Recession Indicators

Introduction

For one of my machine learning classes we had a project that consumed financial data. I have extended that project to use machine learning to see if an indicator, or predictor, can be found that identifies market tops that occur prior to recessions. Then I use the model to build a trading strategy and backtest it to see how it performs.

Get Economic and Financial Data

Acquiring the data consists of two steps. First the code pulls the data into zoo objects which are then collapsed into a single data frame (df.data). Features are extracted from these series and added to the df.data data frame.

Sample call to pull economic data

Data is pulled from several sources include FRED, yahoo, and Google. The code below shows an example that pulls in the consumer price index (CPI) from the FRED. I pull data using quantmod, Quandl, and some manual extractions stored in spreadsheets.

# Consumer Price Index for All Urban Consumers: All Items
if (bRefresh == TRUE) {
  getSymbols("CPIAUCSL", src = "FRED", auto.assign = TRUE)
}

## [1] "CPIAUCSL"

## Warning: ASDAX contains missing values. Some functions will not work if objects
## contain missing values in the middle of the series. Consider using na.omit(),
## na.approx(), na.fill(), etc to remove or replace them.

## Warning: ^TNX contains missing values. Some functions will not work if objects
## contain missing values in the middle of the series. Consider using na.omit(),
## na.approx(), na.fill(), etc to remove or replace them.

## Warning: CL=F contains missing values. Some functions will not work if objects
## contain missing values in the middle of the series. Consider using na.omit(),
## na.approx(), na.fill(), etc to remove or replace them.

## Warning: ^IRX contains missing values. Some functions will not work if objects
## contain missing values in the middle of the series. Consider using na.omit(),
## na.approx(), na.fill(), etc to remove or replace them.

## Warning: ^RLG contains missing values. Some functions will not work if objects
## contain missing values in the middle of the series. Consider using na.omit(),
## na.approx(), na.fill(), etc to remove or replace them.

## Warning: ^STOXX50E contains missing values. Some functions will not work if
## objects contain missing values in the middle of the series. Consider using
## na.omit(), na.approx(), na.fill(), etc to remove or replace them.

## Warning: TMFGX contains missing values. Some functions will not work if objects
## contain missing values in the middle of the series. Consider using na.omit(),
## na.approx(), na.fill(), etc to remove or replace them.

Load rig count data

The Baker Hughes rig count numbers

USDA data

Loading in farm data

## Warning in read_fun(path = enc2native(normalizePath(path)), sheet_i = sheet, :
## Expecting numeric in E3 / R3C5: got a date

## New names:
## * `` -> ...1
## * `` -> ...2
## * `` -> ...3
## * `` -> ...4
## * `` -> ...5
## * ...

## Warning: NAs introduced by coercion

Loading in Silverblatt’s S&P 500 spreadsheet starting with the quarterly data.

## New names:
## * `` -> ...2
## * `` -> ...3
## * `` -> ...5
## * `` -> ...6
## * `` -> ...7

Now load in the estimates

## New names:
## * `` -> ...2
## * `` -> ...3
## * `` -> ...4
## * `` -> ...5
## * `` -> ...6
## * ...

Covid 19 Data

Get the Covid-19 data from JHU

## Rows: 610500 Columns: 15

## -- Column specification ------------------------------------------------------------------------------------------------
## Delimiter: ","
## chr  (8): province, country, type, iso2, iso3, combined_key, continent_name,...
## dbl  (6): lat, long, cases, uid, code3, population
## date (1): date

## 
## i Use `spec()` to retrieve the full column specification for this data.
## i Specify the column types or set `show_col_types = FALSE` to quiet this message.

## Downloading GitHub repo RamiKrispin/coronavirus@master

##   
  
  
v  checking for file 'C:\Users\Rainy\AppData\Local\Temp\RtmpIF8QhO\remotes78b4155e7012\RamiKrispin-coronavirus-f0d703d/DESCRIPTION' (360ms)
## 
  
  
  
-  preparing 'coronavirus': (1.5s)
##    checking DESCRIPTION meta-information ...
  
   checking DESCRIPTION meta-information ... 
  
v  checking DESCRIPTION meta-information
## 
  
  
  
-  checking for LF line-endings in source and make files and shell scripts
## 
  
  
  
-  checking for empty or unneeded directories
## 
  
  
  
-  building 'coronavirus_0.3.32.tar.gz'
## 
  
   
## 

## Caught an warning!

## <simpleWarning: package 'coronavirus' is in use and will not be installed>

## `summarise()` has grouped output by 'country'. You can override using the `.groups` argument.

## Warning: Removed 3 row(s) containing missing values (geom_path).

Feature Extraction

With the raw data downloaded, some of the interesting features can be extracted. The first step is reconcile the time intervals. Some of the data is released monthly and some daily. I chose to interpolate all data to a daily interval. The first section of code adds the daily rows to the dataframe.

The code performs interpolation for continuous data or carries it forward for binary data like the recession indicators.

source("calcInterpolate.r")
df.data <- calcInterpolate(df.data, df.symbols)

## Warning in merge.xts(xtsData, get(df.symbols$string.symbol[idx])): NAs
## introduced by coercion

Truncate data

Create aggregate series

Some analysis requires that two or more series be combined. For example, normallizing debt by GDP to get a sense of the proportion of debt to the total economy helps understand the debt cycle.

Year over year, smoothed derivative, and log trends tend to smooth out seasonal variation. It gets used so often that I do this for every series downloaded.

source("calcFeatures.r")
lst.df <- calcFeatures(df.data, df.symbols)

## [1] "USREC has zero or negative values. Log series will be zero."
## [1] "GSFTX.Volume has zero or negative values. Log series will be zero."
## [1] "LFMIX.Volume has zero or negative values. Log series will be zero."
## [1] "LFMCX.Volume has zero or negative values. Log series will be zero."
## [1] "LFMAX.Volume has zero or negative values. Log series will be zero."
## [1] "LCSIX.Volume has zero or negative values. Log series will be zero."
## [1] "VBIRX.Volume has zero or negative values. Log series will be zero."
## [1] "VFSUX.Volume has zero or negative values. Log series will be zero."
## [1] "LTUIX.Volume has zero or negative values. Log series will be zero."
## [1] "PTTPX.Volume has zero or negative values. Log series will be zero."
## [1] "NERYX.Volume has zero or negative values. Log series will be zero."
## [1] "STIGX.Volume has zero or negative values. Log series will be zero."
## [1] "HLGAX.Volume has zero or negative values. Log series will be zero."
## [1] "FTRGX.Volume has zero or negative values. Log series will be zero."
## [1] "THIIX.Volume has zero or negative values. Log series will be zero."
## [1] "PTTRX.Volume has zero or negative values. Log series will be zero."
## [1] "BFIGX.Volume has zero or negative values. Log series will be zero."
## [1] "EIFAX.Volume has zero or negative values. Log series will be zero."
## [1] "ASDAX.Volume has zero or negative values. Log series will be zero."
## [1] "TRBUX.Volume has zero or negative values. Log series will be zero."
## [1] "PRWCX.Volume has zero or negative values. Log series will be zero."
## [1] "ADOZX.Volume has zero or negative values. Log series will be zero."
## [1] "MERFX.Volume has zero or negative values. Log series will be zero."
## [1] "CMNIX.Volume has zero or negative values. Log series will be zero."
## [1] "CIHEX.Volume has zero or negative values. Log series will be zero."
## [1] "SRPSABSNNCB has zero or negative values. Log series will be zero."
## [1] "TNX.Volume has zero or negative values. Log series will be zero."
## [1] "CLF.Open has zero or negative values. Log series will be zero."
## [1] "CLF.Low has zero or negative values. Log series will be zero."
## [1] "CLF.Close has zero or negative values. Log series will be zero."
## [1] "CLF.Volume has zero or negative values. Log series will be zero."
## [1] "CLF.Adjusted has zero or negative values. Log series will be zero."
## [1] "DTB3 has zero or negative values. Log series will be zero."
## [1] "IRX.Open has zero or negative values. Log series will be zero."
## [1] "IRX.High has zero or negative values. Log series will be zero."
## [1] "IRX.Low has zero or negative values. Log series will be zero."
## [1] "IRX.Close has zero or negative values. Log series will be zero."
## [1] "IRX.Volume has zero or negative values. Log series will be zero."
## [1] "IRX.Adjusted has zero or negative values. Log series will be zero."
## [1] "DCOILWTICO has zero or negative values. Log series will be zero."
## [1] "RLG.Volume has zero or negative values. Log series will be zero."
## [1] "STOXX50E.Volume has zero or negative values. Log series will be zero."
## [1] "GDPNOW has zero or negative values. Log series will be zero."
## [1] "W790RC1Q027SBEA has zero or negative values. Log series will be zero."
## [1] "VXX.Volume has zero or negative values. Log series will be zero."
## [1] "FYFSD has zero or negative values. Log series will be zero."
## [1] "FYFSGDA188S has zero or negative values. Log series will be zero."
## [1] "SOFR25 has zero or negative values. Log series will be zero."
## [1] "SOFR1 has zero or negative values. Log series will be zero."
## [1] "RPONTSYD has zero or negative values. Log series will be zero."
## [1] "BOPGTB has zero or negative values. Log series will be zero."
## [1] "EES.Volume has zero or negative values. Log series will be zero."
## [1] "VGSTX.Volume has zero or negative values. Log series will be zero."
## [1] "VFINX.Volume has zero or negative values. Log series will be zero."
## [1] "TMFGX.Volume has zero or negative values. Log series will be zero."
## [1] "HAINX.Volume has zero or negative values. Log series will be zero."
## [1] "IVOO.Volume has zero or negative values. Log series will be zero."
## [1] "VO.Volume has zero or negative values. Log series will be zero."
## [1] "CZA.Volume has zero or negative values. Log series will be zero."
## [1] "SLY.Volume has zero or negative values. Log series will be zero."
## [1] "HYMB.Volume has zero or negative values. Log series will be zero."
## [1] "GOLD.Open has zero or negative values. Log series will be zero."
## [1] "GOLD.Volume has zero or negative values. Log series will be zero."
## [1] "BKR.Open has zero or negative values. Log series will be zero."
## [1] "BKR.Volume has zero or negative values. Log series will be zero."
## [1] "HAL.Open has zero or negative values. Log series will be zero."
## [1] "HAL.Volume has zero or negative values. Log series will be zero."
## [1] "IP.Open has zero or negative values. Log series will be zero."
## [1] "T.Open has zero or negative values. Log series will be zero."
## [1] "OPEARNINGSPERSHARE has zero or negative values. Log series will be zero."
## [1] "AREARNINGSPERSHARE has zero or negative values. Log series will be zero."
## [1] "OCCEquityVolume has zero or negative values. Log series will be zero."
## [1] "OCCNonEquityVolume has zero or negative values. Log series will be zero."
## [1] "BUSLOANS.minus.BUSLOANSNSA has zero or negative values. Log series will be zero."
## [1] "BUSLOANS.minus.BUSLOANSNSA.by.GDP has zero or negative values. Log series will be zero."
## [1] "EXPCH.minus.IMPCH has zero or negative values. Log series will be zero."
## [1] "EXPMX.minus.IMPMX has zero or negative values. Log series will be zero."
## [1] "SRPSABSNNCB.by.GDP has zero or negative values. Log series will be zero."
## [1] "DGS30TO10 has zero or negative values. Log series will be zero."
## [1] "DGS10TO1 has zero or negative values. Log series will be zero."
## [1] "DGS10TO2 has zero or negative values. Log series will be zero."
## [1] "DGS10TOTB3MS has zero or negative values. Log series will be zero."
## [1] "DGS10TODTB3 has zero or negative values. Log series will be zero."
## [1] "DCOILWTICO.by.PPIACO has zero or negative values. Log series will be zero."
## [1] "GSPC.DailySwing has zero or negative values. Log series will be zero."

df.data <- lst.df[[1]]
df.symbols <- lst.df[[2]]

Recession calculations

Summary calculations

These values are used below

Conclusion

In this worksheet a model predicting the onset of recession was built. From the model a trading rule was derived to allow backtesting. The model performed well and the trading rule backtesting showed that applying this in the post-WWII period would have resulted in an increase in returns. That is not too bad, but there are a few changes that would likely improve the model:

• Go long on short term bonds, rather than just roll out of the market. That way at least some returns would be generated during recessions.
• Refine the recession indicator.

Market Conditions

#The model is predicting a `r paste(sprintf("%3.0f", tail(df.data$recession.initiation.smooth.avg,1)[[1]]*100), "%", sep="")` chance of recession in the next 12 months. :

#- P/E ratio of `r sprintf("%3.2f", tail(df.data$MULTPLSP500PERATIOMONTH,1))` compares to a historical mean value over the last decade of `r sprintf("%3.2f", df.data$MULTPLSP500PERATIOMONTH_Mean[1])`. Since 2008 recession P/E has only fallen below historical norm a few times. The current value is high, but well off the peaks. If earnings are +2-4% year-over-year then it is not unrealistic.

As of Feb 2020 we have entered a recession as defined by the NBER yet the market continues to rise.

P/E ratio of 30.02 compares to a historical mean value over the last decade of 18.62. Since 2008 recession P/E has only fallen below historical norm a few times. The current value is high, but well off the peaks. If earnings are +2-4% year-over-year then it is not unrealistic.

• S&P 500 Volume, last updated on 2022-01-28, is negative over the last year and positive over the last month.

Unemployment

• Headline unemployment (U-3) stands at 3.90% (last updated on 2021-12-01) which is near the 1-year average of 5.05% and rising with respect to the low in the last twelve months of 3.90%. Unlikely the rate will drop again.

• Payrolls (BLS data, NSA) year-over-year stands at 5.71% which is above the 1-year average of 4.49% and falling with respect to the peak, in the last twelve months, of 10.86%.

• Jobless claims (ICSA data) year-over-year stands at -68.94% (last updated on 2022-01-22) which is in-line with the 1-year average of -30.91% and below the peak, in the last twelve months, of 317.48%.

## Warning: Removed 1 rows containing missing values (geom_text).

## Warning: Removed 1 rows containing missing values (geom_hline).

## Warning: Removed 1 rows containing missing values (geom_text).

## Warning: Removed 1 rows containing missing values (geom_hline).

Personal Income

• Real personal income year over year growth stands at 2.24% (last updated on 2021-12-01). This is below the recent peak of 8.49%.

Yield Curve and Bond Market

• The 10-year to 3-month yield stands at 1.61% (last updated on 2022-01-27). This is above the recent low of 1.02%. The trend is flat over the last year and flat over the last month.

• Auto sales flat?

Auxillary Series

I explored additional data series. The sections below have those data series along with comments.

Recent Highs

Print out the new 180 day high values

df.symbolsTrue <-
  df.symbols[df.symbols$'Max180' == TRUE, c("string.symbol", "string.description")]
df.symbolsTrue <-
  df.symbolsTrue[!(is.na(df.symbolsTrue$string.symbol)), ]
df.symbolsTrue <-
  df.symbolsTrue[!(df.symbolsTrue$string.symbol == 'USREC'), ]
#print(head(df.symbolsTrue,20))

kable(df.symbolsTrue, caption = "6-Month High") %>%
  kable_styling(bootstrap_options = c("striped", "hover"))  

6-Month High

	string.symbol	string.description
1	CPIAUCSL	Consumer Price Index for All Urban Consumers: All Items
4	PCEPI	Personal Consumption Expenditures: Chain-type Price Index
7	NPPTTL	Total Nonfarm Private Payroll Employment (ADP)
9	PAYNSA	All Employees: Total Nonfarm Payrolls (NSA)
10	TABSHNO	Households and nonprofit organizations; total assets, Level
11	HNONWPDPI	Household Net Worth, percent Dispsable Income
14	RSALES	Real Retail Sales (DISCONTINUED)
49	IMPCH	U.S. Imports of Goods by Customs Basis from China (Monthly, NSA)
51	IMPMX	U.S. Imports of Goods by Customs Basis from Mexico (Monthly, NSA)
54	HNFSUSNSA	New One Family Houses for Sale in the United States (Monthly, NSA)
55	BUSLOANS	Commercial and Industrial Loans, All Commercial Banks (Monthly, SA)
57	BUSLOANSNSA	Commercial and Industrial Loans, All Commercial Banks (Monthly, NSA)
58	REALLNNSA	Real Estate Loans, All Commercial Banks (Monthly, NSA)
59	REALLN	Real Estate Loans, All Commercial Banks (Monthly, SA)
62	RREACBM027NBOG	Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, NSA)
63	RREACBM027SBOG	Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, SA)
67	CONSUMERNSA	Consumer Loans, All Commercial Banks
69	DPSACBW027SBOG	Deposits, All Commercial Banks
70	DRCLACBS	Delinquency Rate on Consumer Loans, All Commercial Banks, SA
72	SRPSABSNNCB	Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA)
73	ASTLL	All sectors; total loans; liability, Level (NSA)
74	FBDILNECA	Domestic financial sectors; depository institution loans n.e.c.; asset, Level (NSA)
75	ASOLAL	All sectors; other loans and advances; liability, Level (NSA)
76	ASTMA	All sectors; total mortgages; asset, Level (NSA)
77	ASHMA	All sectors; home mortgages; asset, Level (NSA)
78	ASMRMA	All sectors; multifamily residential mortgages; asset, Level (NSA)
79	ASCMA	All sectors; commercial mortgages; asset, Level (NSA)
80	ASFMA	All sectors; farm mortgages; asset, Level (NSA)
81	CCLBSHNO	Households and nonprofit organizations; consumer credit; liability, Level (NSA)
82	FBDSILQ027S	Domestic financial sectors debt securities; liability, Level (NSA)
83	FBLL	Domestic financial sectors loans; liability, Level (NSA)
84	NCBDBIQ027S	Nonfinancial corporate business; debt securities; liability, Level
89	DGS1	1-Year Treasury Constant Maturity Rate
90	DGS2	2-Year Treasury Constant Maturity Rate
91	TB3MS	3-Month Treasury Bill: Secondary Market Rate (Monthly)
92	DTB3	3-Month Treasury Bill: Secondary Market Rate (Daily)
96	NEWORDER	Manufacturers’ New Orders: Nondefense Capital Goods Excluding Aircraft
104	GDP	Gross Domestic Product
105	FNDEFX	Federal Government: Nondefense Consumption Expenditures and Gross Investment (SA, Annual Rate)
108	GDPC1	Real Gross Domestic Product
109	GDPDEF	Gross Domestic Product: Implicit Price Deflator
113	GPDI	Gross Private Domestic Investment
114	W790RC1Q027SBEA	Net domestic investment: Private: Domestic busines
115	MZMV	Velocity of MZM Money Stock
116	M1	M1 Money Stock
117	M2	M2 Money Stock
118	OPHNFB	Nonfarm Business Sector: Real Output Per Hour of All Persons
121	GS5	5-Year Treasury Constant Maturity Rate
126	GFDEBTN	Federal Debt: Total Public Debt
127	HOUST	Housing Starts: Total: New Privately Owned Housing Units Started
129	UMDMNO	Manufacturers’ New Orders: Durable Goods (NSA)
131	CSUSHPINSA	S&P/Case-Shiller U.S. National Home Price Index (NSA)
132	GFDEGDQ188S	Federal Debt: Total Public Debt as Percent of Gross Domestic Product
133	FYFSD	Federal Surplus or Deficit
134	FYFSGDA188S	Federal Surplus or Deficit [-] as Percent of Gross Domestic Product
140	OUTMS	Manufacturing Sector: Real Output
141	MANEMP	All Employees: Manufacturing
142	PRS30006163	Manufacturing Sector: Real Output Per Person
143	BAMLC0A3CA	ICE BofAML US Corporate A Option-Adjusted Spread
145	SOFR	Secured Overnight Financing Rate
147	SOFR99	Secured Overnight Financing Rate: 99th Percentile
154	OBFR25	Overnight Bank Funding Rate: 25th Percentile
155	OBFR1	Overnight Bank Funding Rate: 1st Percentile
157	IOER	Interest Rate on Excess Reserves
159	EXCSRESNW	Excess Reserves of Depository Institutions
160	ECBASSETS	Central Bank Assets for Euro Area (11-19 Countries)
161	EUNNGDP	Gross Domestic Product (Euro/ECU series) for Euro Area (19 Countries)
162	CEU0600000007	Average Weekly Hours of Production and Nonsupervisory Employees: Goods-Producing
164	CURRENCY	Currency Component of M1 (Seasonally Adjusted)
166	BOGMBASE	Monetary Base; Total
167	PRS88003193	Nonfinancial Corporations Sector: Unit Profits
170	POPTHM	Population (U.S.)
171	POPTHM	Population (U.S.)
172	CLF16OV	Civilian Labor Force Level, SA
180	A065RC1A027NBEA	Personal income (NSA)
181	PI	Personal income (SA)
183	A053RC1Q027SBEA	National income: Corporate profits before tax (without IVA and CCAdj)
184	CPROFIT	Corporate Profits with Inventory Valuation Adjustment (IVA) and Capital Consumption Adjustment (CCAdj)
219	MULTPLSP500SALESQUARTER	S&P 500 TTM Sales (Not Inflation Adjusted)
221	MULTPLSP500DIVMONTH	S&P 500 Dividend by Month (Inflation Adjusted)
222	CHRISCMEHG1	Copper Futures, Continuous Contract #1 (HG1) (Front Month)
223	WWDIWLDISAIRGOODMTK1	Air transport, freight
224	BKRTotal	Total Rig Count
225	BKRGas	Gas Rig Count
226	BKROil	Oil Rig Count
227	FARMINCOME	Net Farm Income
228	OPEARNINGSPERSHARE	Operating Earnings per Share
229	AREARNINGSPERSHARE	As-Reported Earnings per Share
230	CASHDIVIDENDSPERSHR	Cash Dividends per Share
231	SALESPERSHR	Sales per Share
232	BOOKVALPERSHR	Book value per Share
233	CAPEXPERSHR	Cap ex per Share
234	PRICE	Price
235	OPEARNINGSTTM	TTM Operating Earnings
236	AREARNINGSTTM	TTM Reported Earnings
238	FINRAFreeCreditMargin	Free Credit Balances in Customers’ Securities Margin Accounts
239	OCCEquityVolume	Equity Options Volume
240	OCCNonEquityVolume	Non-Equity Options Volume
244	BUSLOANS.by.GDP	Business Loans Normalized by GDP
247	BUSLOANSNSA.by.GDP	Business Loans Normalized by GDP
257	CONSUMERNSA.by.GDP	Consumer Loans Not Seasonally Adjusted divided by GDP
262	UMDMNO.by.GDP	Durable Goods (Monthly, NSA) divided by GDP
267	CONSUMERNSA.INTEREST	Consumer Loans (Not Seasonally Adjusted) Interest Burdens
269	TOTLNNSA	Total Loans Not Seasonally Adjusted (BUSLOANS+REALLNSA+CONSUMERNSA)
270	TOTLNNSA.by.GDP	Total Loans Not Seasonally Adjusted divided by GDP
282	ASFMA.by.ASTLL	All sectors; total loans Divided by farm mortgages
288	ECBASSETS.by.EUNNGDP	Central Bank Assets for Euro Area (11-19 Countries) Divided by GDP
297	NPPTTLBYPOPTHM	ADP Private Employment / Population
306	GSG.Close.by.GDPDEF	GSCI Commodity-Indexed Trust, Normalized by GDP def
311	GSPC.CloseBYMDY.Close	GSPC by MDY
316	HNFSUSNSA.minus.HSN1FNSA	Houses for sale - houses sold
317	MSPUS.times.HOUST	New privately owned units start times median price
318	MSPUS.times.HNFSUSNSA	New privately owned 1-family units for sale times median price
322	CPIAUCSL_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Consumer Price Index for All Urban Consumers: All Items
325	CPIAUCSL_Log	Log of Consumer Price Index for All Urban Consumers: All Items
326	CPIAUCSL_mva200	Consumer Price Index for All Urban Consumers: All Items 200 Day MA
327	CPIAUCSL_mva050	Consumer Price Index for All Urban Consumers: All Items 50 Day MA
328	USREC_YoY	NBER based Recession Indicators Year over Year
329	USREC_YoY4	NBER based Recession Indicators 4 Year over 4 Year
330	USREC_YoY5	NBER based Recession Indicators 5 Year over 5 Year
331	USREC_Smooth	Savitsky-Golay Smoothed (p=3, n=365) NBER based Recession Indicators
332	USREC_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15) NBER based Recession Indicators
333	USREC_SmoothDer	Derivative of Smoothed NBER based Recession Indicators
334	USREC_Log	Log of NBER based Recession Indicators
335	USREC_mva200	NBER based Recession Indicators 200 Day MA
336	USREC_mva050	NBER based Recession Indicators 50 Day MA
349	PCEPI_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Personal Consumption Expenditures: Chain-type Price Index
352	PCEPI_Log	Log of Personal Consumption Expenditures: Chain-type Price Index
353	PCEPI_mva200	Personal Consumption Expenditures: Chain-type Price Index 200 Day MA
354	PCEPI_mva050	Personal Consumption Expenditures: Chain-type Price Index 50 Day MA
355	CCSA_YoY	Continued Claims (Insured Unemployment) Year over Year
364	CCNSA_YoY	Continued Claims (Insured Unemployment, NSA) Year over Year
376	NPPTTL_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Total Nonfarm Private Payroll Employment (ADP)
379	NPPTTL_Log	Log of Total Nonfarm Private Payroll Employment (ADP)
380	NPPTTL_mva200	Total Nonfarm Private Payroll Employment (ADP) 200 Day MA
381	NPPTTL_mva050	Total Nonfarm Private Payroll Employment (ADP) 50 Day MA
387	U6RATE_SmoothDer	Derivative of Smoothed Total unemployed + margin + part-time U-6
394	PAYNSA_Smooth	Savitsky-Golay Smoothed (p=3, n=365) All Employees: Total Nonfarm Payrolls (NSA)
397	PAYNSA_Log	Log of All Employees: Total Nonfarm Payrolls (NSA)
398	PAYNSA_mva200	All Employees: Total Nonfarm Payrolls (NSA) 200 Day MA
399	PAYNSA_mva050	All Employees: Total Nonfarm Payrolls (NSA) 50 Day MA
403	TABSHNO_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Households and nonprofit organizations; total assets, Level
406	TABSHNO_Log	Log of Households and nonprofit organizations; total assets, Level
407	TABSHNO_mva200	Households and nonprofit organizations; total assets, Level 200 Day MA
408	TABSHNO_mva050	Households and nonprofit organizations; total assets, Level 50 Day MA
412	HNONWPDPI_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Household Net Worth, percent Dispsable Income
415	HNONWPDPI_Log	Log of Household Net Worth, percent Dispsable Income
416	HNONWPDPI_mva200	Household Net Worth, percent Dispsable Income 200 Day MA
417	HNONWPDPI_mva050	Household Net Worth, percent Dispsable Income 50 Day MA
418	INDPRO_YoY	Industrial Production Index Year over Year
421	INDPRO_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Industrial Production Index
425	INDPRO_mva200	Industrial Production Index 200 Day MA
436	RSALES_YoY	Real Retail Sales (DISCONTINUED) Year over Year
437	RSALES_YoY4	Real Retail Sales (DISCONTINUED) 4 Year over 4 Year
438	RSALES_YoY5	Real Retail Sales (DISCONTINUED) 5 Year over 5 Year
442	RSALES_Log	Log of Real Retail Sales (DISCONTINUED)
443	RSALES_mva200	Real Retail Sales (DISCONTINUED) 200 Day MA
444	RSALES_mva050	Real Retail Sales (DISCONTINUED) 50 Day MA
452	W875RX1_mva200	Real personal income excluding current transfer receipts 200 Day MA
459	RPI_SmoothDer	Derivative of Smoothed Real personal income
466	PCOPPUSDM_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Global price of Copper
468	PCOPPUSDM_SmoothDer	Derivative of Smoothed Global price of Copper
470	PCOPPUSDM_mva200	Global price of Copper 200 Day MA
475	NOBL.Open_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
479	NOBL.Open_mva200	200 Day MA
484	NOBL.High_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
488	NOBL.High_mva200	200 Day MA
493	NOBL.Low_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
502	NOBL.Close_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
506	NOBL.Close_mva200	200 Day MA
511	NOBL.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
513	NOBL.Volume_SmoothDer	Derivative of Smoothed
515	NOBL.Volume_mva200	200 Day MA
516	NOBL.Volume_mva050	50 Day MA
520	NOBL.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
524	NOBL.Adjusted_mva200	200 Day MA
529	SCHD.Open_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
533	SCHD.Open_mva200	200 Day MA
538	SCHD.High_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
542	SCHD.High_mva200	200 Day MA
547	SCHD.Low_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
551	SCHD.Low_mva200	200 Day MA
556	SCHD.Close_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
560	SCHD.Close_mva200	200 Day MA
565	SCHD.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
567	SCHD.Volume_SmoothDer	Derivative of Smoothed
569	SCHD.Volume_mva200	200 Day MA
570	SCHD.Volume_mva050	50 Day MA
574	SCHD.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
578	SCHD.Adjusted_mva200	200 Day MA
619	PFF.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
620	PFF.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
621	PFF.Volume_SmoothDer	Derivative of Smoothed
623	PFF.Volume_mva200	200 Day MA
624	PFF.Volume_mva050	50 Day MA
672	HPI.Volume_YoY5	5 Year over 5 Year
673	HPI.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
674	HPI.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
675	HPI.Volume_SmoothDer	Derivative of Smoothed
676	HPI.Volume_Log	Log of
678	HPI.Volume_mva050	50 Day MA
691	GSFTX.Open_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
695	GSFTX.Open_mva200	200 Day MA
700	GSFTX.High_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
704	GSFTX.High_mva200	200 Day MA
709	GSFTX.Low_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
713	GSFTX.Low_mva200	200 Day MA
718	GSFTX.Close_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
722	GSFTX.Close_mva200	200 Day MA
724	GSFTX.Volume_YoY	Year over Year
725	GSFTX.Volume_YoY4	4 Year over 4 Year
726	GSFTX.Volume_YoY5	5 Year over 5 Year
727	GSFTX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
728	GSFTX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
729	GSFTX.Volume_SmoothDer	Derivative of Smoothed
730	GSFTX.Volume_Log	Log of
731	GSFTX.Volume_mva200	200 Day MA
732	GSFTX.Volume_mva050	50 Day MA
736	GSFTX.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
740	GSFTX.Adjusted_mva200	200 Day MA
778	LFMIX.Volume_YoY	Year over Year
779	LFMIX.Volume_YoY4	4 Year over 4 Year
780	LFMIX.Volume_YoY5	5 Year over 5 Year
781	LFMIX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
782	LFMIX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
783	LFMIX.Volume_SmoothDer	Derivative of Smoothed
784	LFMIX.Volume_Log	Log of
785	LFMIX.Volume_mva200	200 Day MA
786	LFMIX.Volume_mva050	50 Day MA
832	LFMCX.Volume_YoY	Year over Year
833	LFMCX.Volume_YoY4	4 Year over 4 Year
834	LFMCX.Volume_YoY5	5 Year over 5 Year
835	LFMCX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
836	LFMCX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
837	LFMCX.Volume_SmoothDer	Derivative of Smoothed
838	LFMCX.Volume_Log	Log of
839	LFMCX.Volume_mva200	200 Day MA
840	LFMCX.Volume_mva050	50 Day MA
886	LFMAX.Volume_YoY	Year over Year
887	LFMAX.Volume_YoY4	4 Year over 4 Year
888	LFMAX.Volume_YoY5	5 Year over 5 Year
889	LFMAX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
890	LFMAX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
891	LFMAX.Volume_SmoothDer	Derivative of Smoothed
892	LFMAX.Volume_Log	Log of
893	LFMAX.Volume_mva200	200 Day MA
894	LFMAX.Volume_mva050	50 Day MA
940	LCSIX.Volume_YoY	Year over Year
941	LCSIX.Volume_YoY4	4 Year over 4 Year
942	LCSIX.Volume_YoY5	5 Year over 5 Year
943	LCSIX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
944	LCSIX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
945	LCSIX.Volume_SmoothDer	Derivative of Smoothed
946	LCSIX.Volume_Log	Log of
947	LCSIX.Volume_mva200	200 Day MA
948	LCSIX.Volume_mva050	50 Day MA
952	LCSIX.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
956	LCSIX.Adjusted_mva200	200 Day MA
957	LCSIX.Adjusted_mva050	50 Day MA
997	BSV.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
998	BSV.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
999	BSV.Volume_SmoothDer	Derivative of Smoothed
1000	BSV.Volume_Log	Log of
1001	BSV.Volume_mva200	200 Day MA
1048	VBIRX.Volume_YoY	Year over Year
1049	VBIRX.Volume_YoY4	4 Year over 4 Year
1050	VBIRX.Volume_YoY5	5 Year over 5 Year
1051	VBIRX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1052	VBIRX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1053	VBIRX.Volume_SmoothDer	Derivative of Smoothed
1054	VBIRX.Volume_Log	Log of
1055	VBIRX.Volume_mva200	200 Day MA
1056	VBIRX.Volume_mva050	50 Day MA
1105	BIV.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1107	BIV.Volume_SmoothDer	Derivative of Smoothed
1110	BIV.Volume_mva050	50 Day MA
1156	VFSUX.Volume_YoY	Year over Year
1157	VFSUX.Volume_YoY4	4 Year over 4 Year
1158	VFSUX.Volume_YoY5	5 Year over 5 Year
1159	VFSUX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1160	VFSUX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1161	VFSUX.Volume_SmoothDer	Derivative of Smoothed
1162	VFSUX.Volume_Log	Log of
1163	VFSUX.Volume_mva200	200 Day MA
1164	VFSUX.Volume_mva050	50 Day MA
1210	LTUIX.Volume_YoY	Year over Year
1211	LTUIX.Volume_YoY4	4 Year over 4 Year
1212	LTUIX.Volume_YoY5	5 Year over 5 Year
1213	LTUIX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1214	LTUIX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1215	LTUIX.Volume_SmoothDer	Derivative of Smoothed
1216	LTUIX.Volume_Log	Log of
1217	LTUIX.Volume_mva200	200 Day MA
1218	LTUIX.Volume_mva050	50 Day MA
1264	PTTPX.Volume_YoY	Year over Year
1265	PTTPX.Volume_YoY4	4 Year over 4 Year
1266	PTTPX.Volume_YoY5	5 Year over 5 Year
1267	PTTPX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1268	PTTPX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1269	PTTPX.Volume_SmoothDer	Derivative of Smoothed
1270	PTTPX.Volume_Log	Log of
1271	PTTPX.Volume_mva200	200 Day MA
1272	PTTPX.Volume_mva050	50 Day MA
1318	NERYX.Volume_YoY	Year over Year
1319	NERYX.Volume_YoY4	4 Year over 4 Year
1320	NERYX.Volume_YoY5	5 Year over 5 Year
1321	NERYX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1322	NERYX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1323	NERYX.Volume_SmoothDer	Derivative of Smoothed
1324	NERYX.Volume_Log	Log of
1325	NERYX.Volume_mva200	200 Day MA
1326	NERYX.Volume_mva050	50 Day MA
1372	STIGX.Volume_YoY	Year over Year
1373	STIGX.Volume_YoY4	4 Year over 4 Year
1374	STIGX.Volume_YoY5	5 Year over 5 Year
1375	STIGX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1376	STIGX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1377	STIGX.Volume_SmoothDer	Derivative of Smoothed
1378	STIGX.Volume_Log	Log of
1379	STIGX.Volume_mva200	200 Day MA
1380	STIGX.Volume_mva050	50 Day MA
1426	HLGAX.Volume_YoY	Year over Year
1427	HLGAX.Volume_YoY4	4 Year over 4 Year
1428	HLGAX.Volume_YoY5	5 Year over 5 Year
1429	HLGAX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1430	HLGAX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1431	HLGAX.Volume_SmoothDer	Derivative of Smoothed
1432	HLGAX.Volume_Log	Log of
1433	HLGAX.Volume_mva200	200 Day MA
1434	HLGAX.Volume_mva050	50 Day MA
1480	FTRGX.Volume_YoY	Year over Year
1481	FTRGX.Volume_YoY4	4 Year over 4 Year
1482	FTRGX.Volume_YoY5	5 Year over 5 Year
1483	FTRGX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1484	FTRGX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1485	FTRGX.Volume_SmoothDer	Derivative of Smoothed
1486	FTRGX.Volume_Log	Log of
1487	FTRGX.Volume_mva200	200 Day MA
1488	FTRGX.Volume_mva050	50 Day MA
1534	THIIX.Volume_YoY	Year over Year
1535	THIIX.Volume_YoY4	4 Year over 4 Year
1536	THIIX.Volume_YoY5	5 Year over 5 Year
1537	THIIX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1538	THIIX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1539	THIIX.Volume_SmoothDer	Derivative of Smoothed
1540	THIIX.Volume_Log	Log of
1541	THIIX.Volume_mva200	200 Day MA
1542	THIIX.Volume_mva050	50 Day MA
1588	PTTRX.Volume_YoY	Year over Year
1589	PTTRX.Volume_YoY4	4 Year over 4 Year
1590	PTTRX.Volume_YoY5	5 Year over 5 Year
1591	PTTRX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1592	PTTRX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1593	PTTRX.Volume_SmoothDer	Derivative of Smoothed
1594	PTTRX.Volume_Log	Log of
1595	PTTRX.Volume_mva200	200 Day MA
1596	PTTRX.Volume_mva050	50 Day MA
1642	BFIGX.Volume_YoY	Year over Year
1643	BFIGX.Volume_YoY4	4 Year over 4 Year
1644	BFIGX.Volume_YoY5	5 Year over 5 Year
1645	BFIGX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1646	BFIGX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1647	BFIGX.Volume_SmoothDer	Derivative of Smoothed
1648	BFIGX.Volume_Log	Log of
1649	BFIGX.Volume_mva200	200 Day MA
1650	BFIGX.Volume_mva050	50 Day MA
1658	BFIGX.Adjusted_mva200	200 Day MA
1665	VTWO.Open_SmoothDer	Derivative of Smoothed
1674	VTWO.High_SmoothDer	Derivative of Smoothed
1699	VTWO.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1701	VTWO.Volume_SmoothDer	Derivative of Smoothed
1704	VTWO.Volume_mva050	50 Day MA
1710	VTWO.Adjusted_SmoothDer	Derivative of Smoothed
1719	EIFAX.Open_SmoothDer	Derivative of Smoothed
1728	EIFAX.High_SmoothDer	Derivative of Smoothed
1737	EIFAX.Low_SmoothDer	Derivative of Smoothed
1746	EIFAX.Close_SmoothDer	Derivative of Smoothed
1750	EIFAX.Volume_YoY	Year over Year
1751	EIFAX.Volume_YoY4	4 Year over 4 Year
1752	EIFAX.Volume_YoY5	5 Year over 5 Year
1753	EIFAX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1754	EIFAX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1755	EIFAX.Volume_SmoothDer	Derivative of Smoothed
1756	EIFAX.Volume_Log	Log of
1757	EIFAX.Volume_mva200	200 Day MA
1758	EIFAX.Volume_mva050	50 Day MA
1762	EIFAX.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1764	EIFAX.Adjusted_SmoothDer	Derivative of Smoothed
1766	EIFAX.Adjusted_mva200	200 Day MA
1767	EIFAX.Adjusted_mva050	50 Day MA
1804	ASDAX.Volume_YoY	Year over Year
1805	ASDAX.Volume_YoY4	4 Year over 4 Year
1806	ASDAX.Volume_YoY5	5 Year over 5 Year
1807	ASDAX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1808	ASDAX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1809	ASDAX.Volume_SmoothDer	Derivative of Smoothed
1810	ASDAX.Volume_Log	Log of
1811	ASDAX.Volume_mva200	200 Day MA
1812	ASDAX.Volume_mva050	50 Day MA
1858	TRBUX.Volume_YoY	Year over Year
1859	TRBUX.Volume_YoY4	4 Year over 4 Year
1860	TRBUX.Volume_YoY5	5 Year over 5 Year
1861	TRBUX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1862	TRBUX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1863	TRBUX.Volume_SmoothDer	Derivative of Smoothed
1864	TRBUX.Volume_Log	Log of
1865	TRBUX.Volume_mva200	200 Day MA
1866	TRBUX.Volume_mva050	50 Day MA
1912	PRWCX.Volume_YoY	Year over Year
1913	PRWCX.Volume_YoY4	4 Year over 4 Year
1914	PRWCX.Volume_YoY5	5 Year over 5 Year
1915	PRWCX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1916	PRWCX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1917	PRWCX.Volume_SmoothDer	Derivative of Smoothed
1918	PRWCX.Volume_Log	Log of
1919	PRWCX.Volume_mva200	200 Day MA
1920	PRWCX.Volume_mva050	50 Day MA
1928	PRWCX.Adjusted_mva200	200 Day MA
1966	ADOZX.Volume_YoY	Year over Year
1967	ADOZX.Volume_YoY4	4 Year over 4 Year
1968	ADOZX.Volume_YoY5	5 Year over 5 Year
1969	ADOZX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
1970	ADOZX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
1971	ADOZX.Volume_SmoothDer	Derivative of Smoothed
1972	ADOZX.Volume_Log	Log of
1973	ADOZX.Volume_mva200	200 Day MA
1974	ADOZX.Volume_mva050	50 Day MA
1989	MERFX.Open_SmoothDer	Derivative of Smoothed
1998	MERFX.High_SmoothDer	Derivative of Smoothed
2007	MERFX.Low_SmoothDer	Derivative of Smoothed
2016	MERFX.Close_SmoothDer	Derivative of Smoothed
2020	MERFX.Volume_YoY	Year over Year
2021	MERFX.Volume_YoY4	4 Year over 4 Year
2022	MERFX.Volume_YoY5	5 Year over 5 Year
2023	MERFX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2024	MERFX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
2025	MERFX.Volume_SmoothDer	Derivative of Smoothed
2026	MERFX.Volume_Log	Log of
2027	MERFX.Volume_mva200	200 Day MA
2028	MERFX.Volume_mva050	50 Day MA
2034	MERFX.Adjusted_SmoothDer	Derivative of Smoothed
2045	CMNIX.Open_mva200	200 Day MA
2054	CMNIX.High_mva200	200 Day MA
2063	CMNIX.Low_mva200	200 Day MA
2072	CMNIX.Close_mva200	200 Day MA
2074	CMNIX.Volume_YoY	Year over Year
2075	CMNIX.Volume_YoY4	4 Year over 4 Year
2076	CMNIX.Volume_YoY5	5 Year over 5 Year
2077	CMNIX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2078	CMNIX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
2079	CMNIX.Volume_SmoothDer	Derivative of Smoothed
2080	CMNIX.Volume_Log	Log of
2081	CMNIX.Volume_mva200	200 Day MA
2082	CMNIX.Volume_mva050	50 Day MA
2090	CMNIX.Adjusted_mva200	200 Day MA
2099	CIHEX.Open_mva200	200 Day MA
2108	CIHEX.High_mva200	200 Day MA
2117	CIHEX.Low_mva200	200 Day MA
2126	CIHEX.Close_mva200	200 Day MA
2128	CIHEX.Volume_YoY	Year over Year
2129	CIHEX.Volume_YoY4	4 Year over 4 Year
2130	CIHEX.Volume_YoY5	5 Year over 5 Year
2131	CIHEX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2132	CIHEX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
2133	CIHEX.Volume_SmoothDer	Derivative of Smoothed
2134	CIHEX.Volume_Log	Log of
2135	CIHEX.Volume_mva200	200 Day MA
2136	CIHEX.Volume_mva050	50 Day MA
2140	CIHEX.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2144	CIHEX.Adjusted_mva200	200 Day MA
2146	IMPCH_YoY	U.S. Imports of Goods by Customs Basis from China (Monthly, NSA) Year over Year
2147	IMPCH_YoY4	U.S. Imports of Goods by Customs Basis from China (Monthly, NSA) 4 Year over 4 Year
2148	IMPCH_YoY5	U.S. Imports of Goods by Customs Basis from China (Monthly, NSA) 5 Year over 5 Year
2152	IMPCH_Log	Log of U.S. Imports of Goods by Customs Basis from China (Monthly, NSA)
2153	IMPCH_mva200	U.S. Imports of Goods by Customs Basis from China (Monthly, NSA) 200 Day MA
2154	IMPCH_mva050	U.S. Imports of Goods by Customs Basis from China (Monthly, NSA) 50 Day MA
2155	EXPCH_YoY	U.S. Exports of Goods by F.A.S. Basis to China, Mainland (Monthly, NSA) Year over Year
2156	EXPCH_YoY4	U.S. Exports of Goods by F.A.S. Basis to China, Mainland (Monthly, NSA) 4 Year over 4 Year
2157	EXPCH_YoY5	U.S. Exports of Goods by F.A.S. Basis to China, Mainland (Monthly, NSA) 5 Year over 5 Year
2158	EXPCH_Smooth	Savitsky-Golay Smoothed (p=3, n=365) U.S. Exports of Goods by F.A.S. Basis to China, Mainland (Monthly, NSA)
2160	EXPCH_SmoothDer	Derivative of Smoothed U.S. Exports of Goods by F.A.S. Basis to China, Mainland (Monthly, NSA)
2162	EXPCH_mva200	U.S. Exports of Goods by F.A.S. Basis to China, Mainland (Monthly, NSA) 200 Day MA
2164	IMPMX_YoY	U.S. Imports of Goods by Customs Basis from Mexico (Monthly, NSA) Year over Year
2167	IMPMX_Smooth	Savitsky-Golay Smoothed (p=3, n=365) U.S. Imports of Goods by Customs Basis from Mexico (Monthly, NSA)
2170	IMPMX_Log	Log of U.S. Imports of Goods by Customs Basis from Mexico (Monthly, NSA)
2171	IMPMX_mva200	U.S. Imports of Goods by Customs Basis from Mexico (Monthly, NSA) 200 Day MA
2172	IMPMX_mva050	U.S. Imports of Goods by Customs Basis from Mexico (Monthly, NSA) 50 Day MA
2175	EXPMX_YoY5	U.S. Exports of Goods by F.A.S. Basis to Mexico (Monthly, NSA) 5 Year over 5 Year
2176	EXPMX_Smooth	Savitsky-Golay Smoothed (p=3, n=365) U.S. Exports of Goods by F.A.S. Basis to Mexico (Monthly, NSA)
2180	EXPMX_mva200	U.S. Exports of Goods by F.A.S. Basis to Mexico (Monthly, NSA) 200 Day MA
2185	HSN1FNSA_Smooth	Savitsky-Golay Smoothed (p=3, n=365) New One Family Houses Sold: United States (Monthly, NSA)
2187	HSN1FNSA_SmoothDer	Derivative of Smoothed New One Family Houses Sold: United States (Monthly, NSA)
2197	HNFSUSNSA_Log	Log of New One Family Houses for Sale in the United States (Monthly, NSA)
2198	HNFSUSNSA_mva200	New One Family Houses for Sale in the United States (Monthly, NSA) 200 Day MA
2199	HNFSUSNSA_mva050	New One Family Houses for Sale in the United States (Monthly, NSA) 50 Day MA
2202	BUSLOANS_YoY5	Commercial and Industrial Loans, All Commercial Banks (Monthly, SA) 5 Year over 5 Year
2203	BUSLOANS_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Commercial and Industrial Loans, All Commercial Banks (Monthly, SA)
2205	BUSLOANS_SmoothDer	Derivative of Smoothed Commercial and Industrial Loans, All Commercial Banks (Monthly, SA)
2206	BUSLOANS_Log	Log of Commercial and Industrial Loans, All Commercial Banks (Monthly, SA)
2208	BUSLOANS_mva050	Commercial and Industrial Loans, All Commercial Banks (Monthly, SA) 50 Day MA
2212	TOTCI_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Commercial and Industrial Loans, All Commercial Banks (Weekly, SA)
2214	TOTCI_SmoothDer	Derivative of Smoothed Commercial and Industrial Loans, All Commercial Banks (Weekly, SA)
2217	TOTCI_mva050	Commercial and Industrial Loans, All Commercial Banks (Weekly, SA) 50 Day MA
2221	BUSLOANSNSA_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Commercial and Industrial Loans, All Commercial Banks (Monthly, NSA)
2223	BUSLOANSNSA_SmoothDer	Derivative of Smoothed Commercial and Industrial Loans, All Commercial Banks (Monthly, NSA)
2224	BUSLOANSNSA_Log	Log of Commercial and Industrial Loans, All Commercial Banks (Monthly, NSA)
2226	BUSLOANSNSA_mva050	Commercial and Industrial Loans, All Commercial Banks (Monthly, NSA) 50 Day MA
2227	REALLNNSA_YoY	Real Estate Loans, All Commercial Banks (Monthly, NSA) Year over Year
2233	REALLNNSA_Log	Log of Real Estate Loans, All Commercial Banks (Monthly, NSA)
2234	REALLNNSA_mva200	Real Estate Loans, All Commercial Banks (Monthly, NSA) 200 Day MA
2235	REALLNNSA_mva050	Real Estate Loans, All Commercial Banks (Monthly, NSA) 50 Day MA
2239	REALLN_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Real Estate Loans, All Commercial Banks (Monthly, SA)
2242	REALLN_Log	Log of Real Estate Loans, All Commercial Banks (Monthly, SA)
2243	REALLN_mva200	Real Estate Loans, All Commercial Banks (Monthly, SA) 200 Day MA
2244	REALLN_mva050	Real Estate Loans, All Commercial Banks (Monthly, SA) 50 Day MA
2248	RELACBW027NBOG_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Real Estate Loans, All Commercial Banks (Weekly, NSA)
2250	RELACBW027NBOG_SmoothDer	Derivative of Smoothed Real Estate Loans, All Commercial Banks (Weekly, NSA)
2252	RELACBW027NBOG_mva200	Real Estate Loans, All Commercial Banks (Weekly, NSA) 200 Day MA
2253	RELACBW027NBOG_mva050	Real Estate Loans, All Commercial Banks (Weekly, NSA) 50 Day MA
2254	RELACBW027SBOG_YoY	Real Estate Loans, All Commercial Banks (Weekly, SA) Year over Year
2257	RELACBW027SBOG_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Real Estate Loans, All Commercial Banks (Weekly, SA)
2259	RELACBW027SBOG_SmoothDer	Derivative of Smoothed Real Estate Loans, All Commercial Banks (Weekly, SA)
2261	RELACBW027SBOG_mva200	Real Estate Loans, All Commercial Banks (Weekly, SA) 200 Day MA
2262	RELACBW027SBOG_mva050	Real Estate Loans, All Commercial Banks (Weekly, SA) 50 Day MA
2263	RREACBM027NBOG_YoY	Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, NSA) Year over Year
2264	RREACBM027NBOG_YoY4	Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, NSA) 4 Year over 4 Year
2265	RREACBM027NBOG_YoY5	Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, NSA) 5 Year over 5 Year
2269	RREACBM027NBOG_Log	Log of Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, NSA)
2270	RREACBM027NBOG_mva200	Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, NSA) 200 Day MA
2271	RREACBM027NBOG_mva050	Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, NSA) 50 Day MA
2272	RREACBM027SBOG_YoY	Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, SA) Year over Year
2274	RREACBM027SBOG_YoY5	Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, SA) 5 Year over 5 Year
2277	RREACBM027SBOG_SmoothDer	Derivative of Smoothed Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, SA)
2278	RREACBM027SBOG_Log	Log of Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, SA)
2279	RREACBM027SBOG_mva200	Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, SA) 200 Day MA
2280	RREACBM027SBOG_mva050	Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, SA) 50 Day MA
2281	RREACBW027SBOG_YoY	Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, SA) Year over Year
2284	RREACBW027SBOG_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, SA)
2286	RREACBW027SBOG_SmoothDer	Derivative of Smoothed Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, SA)
2288	RREACBW027SBOG_mva200	Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, SA) 200 Day MA
2289	RREACBW027SBOG_mva050	Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, SA) 50 Day MA
2295	RREACBW027NBOG_SmoothDer	Derivative of Smoothed Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, NSA)
2297	RREACBW027NBOG_mva200	Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, NSA) 200 Day MA
2299	MORTGAGE30US_YoY	30-Year Fixed Rate Mortgage Average in the United States Year over Year
2302	MORTGAGE30US_Smooth	Savitsky-Golay Smoothed (p=3, n=365) 30-Year Fixed Rate Mortgage Average in the United States
2304	MORTGAGE30US_SmoothDer	Derivative of Smoothed 30-Year Fixed Rate Mortgage Average in the United States
2306	MORTGAGE30US_mva200	30-Year Fixed Rate Mortgage Average in the United States 200 Day MA
2307	MORTGAGE30US_mva050	30-Year Fixed Rate Mortgage Average in the United States 50 Day MA
2308	CONSUMERNSA_YoY	Consumer Loans, All Commercial Banks Year over Year
2309	CONSUMERNSA_YoY4	Consumer Loans, All Commercial Banks 4 Year over 4 Year
2310	CONSUMERNSA_YoY5	Consumer Loans, All Commercial Banks 5 Year over 5 Year
2311	CONSUMERNSA_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Consumer Loans, All Commercial Banks
2314	CONSUMERNSA_Log	Log of Consumer Loans, All Commercial Banks
2315	CONSUMERNSA_mva200	Consumer Loans, All Commercial Banks 200 Day MA
2316	CONSUMERNSA_mva050	Consumer Loans, All Commercial Banks 50 Day MA
2320	TOTLLNSA_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Loans and Leases in Bank Credit, All Commercial Banks
2322	TOTLLNSA_SmoothDer	Derivative of Smoothed Loans and Leases in Bank Credit, All Commercial Banks
2324	TOTLLNSA_mva200	Loans and Leases in Bank Credit, All Commercial Banks 200 Day MA
2325	TOTLLNSA_mva050	Loans and Leases in Bank Credit, All Commercial Banks 50 Day MA
2329	DPSACBW027SBOG_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Deposits, All Commercial Banks
2332	DPSACBW027SBOG_Log	Log of Deposits, All Commercial Banks
2333	DPSACBW027SBOG_mva200	Deposits, All Commercial Banks 200 Day MA
2334	DPSACBW027SBOG_mva050	Deposits, All Commercial Banks 50 Day MA
2335	DRCLACBS_YoY	Delinquency Rate on Consumer Loans, All Commercial Banks, SA Year over Year
2336	DRCLACBS_YoY4	Delinquency Rate on Consumer Loans, All Commercial Banks, SA 4 Year over 4 Year
2337	DRCLACBS_YoY5	Delinquency Rate on Consumer Loans, All Commercial Banks, SA 5 Year over 5 Year
2341	DRCLACBS_Log	Log of Delinquency Rate on Consumer Loans, All Commercial Banks, SA
2342	DRCLACBS_mva200	Delinquency Rate on Consumer Loans, All Commercial Banks, SA 200 Day MA
2343	DRCLACBS_mva050	Delinquency Rate on Consumer Loans, All Commercial Banks, SA 50 Day MA
2347	TOTCINSA_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Commercial and Industrial Loans, All Commercial Banks (Weekly, NSA)
2349	TOTCINSA_SmoothDer	Derivative of Smoothed Commercial and Industrial Loans, All Commercial Banks (Weekly, NSA)
2352	TOTCINSA_mva050	Commercial and Industrial Loans, All Commercial Banks (Weekly, NSA) 50 Day MA
2354	SRPSABSNNCB_YoY4	Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) 4 Year over 4 Year
2355	SRPSABSNNCB_YoY5	Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) 5 Year over 5 Year
2356	SRPSABSNNCB_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA)
2359	SRPSABSNNCB_Log	Log of Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA)
2368	ASTLL_Log	Log of All sectors; total loans; liability, Level (NSA)
2369	ASTLL_mva200	All sectors; total loans; liability, Level (NSA) 200 Day MA
2370	ASTLL_mva050	All sectors; total loans; liability, Level (NSA) 50 Day MA
2374	FBDILNECA_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Domestic financial sectors; depository institution loans n.e.c.; asset, Level (NSA)
2376	FBDILNECA_SmoothDer	Derivative of Smoothed Domestic financial sectors; depository institution loans n.e.c.; asset, Level (NSA)
2377	FBDILNECA_Log	Log of Domestic financial sectors; depository institution loans n.e.c.; asset, Level (NSA)
2386	ASOLAL_Log	Log of All sectors; other loans and advances; liability, Level (NSA)
2387	ASOLAL_mva200	All sectors; other loans and advances; liability, Level (NSA) 200 Day MA
2388	ASOLAL_mva050	All sectors; other loans and advances; liability, Level (NSA) 50 Day MA
2395	ASTMA_Log	Log of All sectors; total mortgages; asset, Level (NSA)
2396	ASTMA_mva200	All sectors; total mortgages; asset, Level (NSA) 200 Day MA
2397	ASTMA_mva050	All sectors; total mortgages; asset, Level (NSA) 50 Day MA
2404	ASHMA_Log	Log of All sectors; home mortgages; asset, Level (NSA)
2405	ASHMA_mva200	All sectors; home mortgages; asset, Level (NSA) 200 Day MA
2406	ASHMA_mva050	All sectors; home mortgages; asset, Level (NSA) 50 Day MA
2413	ASMRMA_Log	Log of All sectors; multifamily residential mortgages; asset, Level (NSA)
2414	ASMRMA_mva200	All sectors; multifamily residential mortgages; asset, Level (NSA) 200 Day MA
2415	ASMRMA_mva050	All sectors; multifamily residential mortgages; asset, Level (NSA) 50 Day MA
2422	ASCMA_Log	Log of All sectors; commercial mortgages; asset, Level (NSA)
2423	ASCMA_mva200	All sectors; commercial mortgages; asset, Level (NSA) 200 Day MA
2424	ASCMA_mva050	All sectors; commercial mortgages; asset, Level (NSA) 50 Day MA
2431	ASFMA_Log	Log of All sectors; farm mortgages; asset, Level (NSA)
2432	ASFMA_mva200	All sectors; farm mortgages; asset, Level (NSA) 200 Day MA
2433	ASFMA_mva050	All sectors; farm mortgages; asset, Level (NSA) 50 Day MA
2440	CCLBSHNO_Log	Log of Households and nonprofit organizations; consumer credit; liability, Level (NSA)
2441	CCLBSHNO_mva200	Households and nonprofit organizations; consumer credit; liability, Level (NSA) 200 Day MA
2442	CCLBSHNO_mva050	Households and nonprofit organizations; consumer credit; liability, Level (NSA) 50 Day MA
2446	FBDSILQ027S_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Domestic financial sectors debt securities; liability, Level (NSA)
2449	FBDSILQ027S_Log	Log of Domestic financial sectors debt securities; liability, Level (NSA)
2450	FBDSILQ027S_mva200	Domestic financial sectors debt securities; liability, Level (NSA) 200 Day MA
2451	FBDSILQ027S_mva050	Domestic financial sectors debt securities; liability, Level (NSA) 50 Day MA
2455	FBLL_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Domestic financial sectors loans; liability, Level (NSA)
2458	FBLL_Log	Log of Domestic financial sectors loans; liability, Level (NSA)
2459	FBLL_mva200	Domestic financial sectors loans; liability, Level (NSA) 200 Day MA
2460	FBLL_mva050	Domestic financial sectors loans; liability, Level (NSA) 50 Day MA
2467	NCBDBIQ027S_Log	Log of Nonfinancial corporate business; debt securities; liability, Level
2468	NCBDBIQ027S_mva200	Nonfinancial corporate business; debt securities; liability, Level 200 Day MA
2469	NCBDBIQ027S_mva050	Nonfinancial corporate business; debt securities; liability, Level 50 Day MA
2473	DGS10_Smooth	Savitsky-Golay Smoothed (p=3, n=365) 10-Year Treasury Constant Maturity Rate
2474	DGS10_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15) 10-Year Treasury Constant Maturity Rate
2475	DGS10_SmoothDer	Derivative of Smoothed 10-Year Treasury Constant Maturity Rate
2478	DGS10_mva050	10-Year Treasury Constant Maturity Rate 50 Day MA
2482	TNX.Open_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2483	TNX.Open_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
2484	TNX.Open_SmoothDer	Derivative of Smoothed
2487	TNX.Open_mva050	50 Day MA
2491	TNX.High_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2492	TNX.High_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
2493	TNX.High_SmoothDer	Derivative of Smoothed
2496	TNX.High_mva050	50 Day MA
2500	TNX.Low_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2501	TNX.Low_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
2502	TNX.Low_SmoothDer	Derivative of Smoothed
2505	TNX.Low_mva050	50 Day MA
2509	TNX.Close_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2511	TNX.Close_SmoothDer	Derivative of Smoothed
2514	TNX.Close_mva050	50 Day MA
2515	TNX.Volume_YoY	Year over Year
2516	TNX.Volume_YoY4	4 Year over 4 Year
2517	TNX.Volume_YoY5	5 Year over 5 Year
2518	TNX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2519	TNX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
2520	TNX.Volume_SmoothDer	Derivative of Smoothed
2521	TNX.Volume_Log	Log of
2522	TNX.Volume_mva200	200 Day MA
2523	TNX.Volume_mva050	50 Day MA
2527	TNX.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2529	TNX.Adjusted_SmoothDer	Derivative of Smoothed
2532	TNX.Adjusted_mva050	50 Day MA
2536	CLF.Open_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2537	CLF.Open_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
2539	CLF.Open_Log	Log of
2540	CLF.Open_mva200	200 Day MA
2545	CLF.High_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2546	CLF.High_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
2548	CLF.High_Log	Log of
2549	CLF.High_mva200	200 Day MA
2554	CLF.Low_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2555	CLF.Low_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
2557	CLF.Low_Log	Log of
2558	CLF.Low_mva200	200 Day MA
2563	CLF.Close_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2564	CLF.Close_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
2566	CLF.Close_Log	Log of
2567	CLF.Close_mva200	200 Day MA
2574	CLF.Volume_SmoothDer	Derivative of Smoothed
2575	CLF.Volume_Log	Log of
2581	CLF.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2582	CLF.Adjusted_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
2584	CLF.Adjusted_Log	Log of
2585	CLF.Adjusted_mva200	200 Day MA
2590	DGS30_Smooth	Savitsky-Golay Smoothed (p=3, n=365) 10-Year Treasury Constant Maturity Rate
2592	DGS30_SmoothDer	Derivative of Smoothed 10-Year Treasury Constant Maturity Rate
2599	DGS1_Smooth	Savitsky-Golay Smoothed (p=3, n=365) 1-Year Treasury Constant Maturity Rate
2600	DGS1_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15) 1-Year Treasury Constant Maturity Rate
2601	DGS1_SmoothDer	Derivative of Smoothed 1-Year Treasury Constant Maturity Rate
2602	DGS1_Log	Log of 1-Year Treasury Constant Maturity Rate
2603	DGS1_mva200	1-Year Treasury Constant Maturity Rate 200 Day MA
2604	DGS1_mva050	1-Year Treasury Constant Maturity Rate 50 Day MA
2605	DGS2_YoY	2-Year Treasury Constant Maturity Rate Year over Year
2607	DGS2_YoY5	2-Year Treasury Constant Maturity Rate 5 Year over 5 Year
2608	DGS2_Smooth	Savitsky-Golay Smoothed (p=3, n=365) 2-Year Treasury Constant Maturity Rate
2609	DGS2_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15) 2-Year Treasury Constant Maturity Rate
2610	DGS2_SmoothDer	Derivative of Smoothed 2-Year Treasury Constant Maturity Rate
2611	DGS2_Log	Log of 2-Year Treasury Constant Maturity Rate
2612	DGS2_mva200	2-Year Treasury Constant Maturity Rate 200 Day MA
2613	DGS2_mva050	2-Year Treasury Constant Maturity Rate 50 Day MA
2614	TB3MS_YoY	3-Month Treasury Bill: Secondary Market Rate (Monthly) Year over Year
2620	TB3MS_Log	Log of 3-Month Treasury Bill: Secondary Market Rate (Monthly)
2621	TB3MS_mva200	3-Month Treasury Bill: Secondary Market Rate (Monthly) 200 Day MA
2622	TB3MS_mva050	3-Month Treasury Bill: Secondary Market Rate (Monthly) 50 Day MA
2626	DTB3_Smooth	Savitsky-Golay Smoothed (p=3, n=365) 3-Month Treasury Bill: Secondary Market Rate (Daily)
2628	DTB3_SmoothDer	Derivative of Smoothed 3-Month Treasury Bill: Secondary Market Rate (Daily)
2629	DTB3_Log	Log of 3-Month Treasury Bill: Secondary Market Rate (Daily)
2630	DTB3_mva200	3-Month Treasury Bill: Secondary Market Rate (Daily) 200 Day MA
2631	DTB3_mva050	3-Month Treasury Bill: Secondary Market Rate (Daily) 50 Day MA
2632	IRX.Open_YoY	Year over Year
2635	IRX.Open_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2636	IRX.Open_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
2637	IRX.Open_SmoothDer	Derivative of Smoothed
2638	IRX.Open_Log	Log of
2639	IRX.Open_mva200	200 Day MA
2640	IRX.Open_mva050	50 Day MA
2641	IRX.High_YoY	Year over Year
2644	IRX.High_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2645	IRX.High_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
2646	IRX.High_SmoothDer	Derivative of Smoothed
2647	IRX.High_Log	Log of
2648	IRX.High_mva200	200 Day MA
2649	IRX.High_mva050	50 Day MA
2650	IRX.Low_YoY	Year over Year
2653	IRX.Low_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2655	IRX.Low_SmoothDer	Derivative of Smoothed
2656	IRX.Low_Log	Log of
2657	IRX.Low_mva200	200 Day MA
2658	IRX.Low_mva050	50 Day MA
2659	IRX.Close_YoY	Year over Year
2662	IRX.Close_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2664	IRX.Close_SmoothDer	Derivative of Smoothed
2665	IRX.Close_Log	Log of
2666	IRX.Close_mva200	200 Day MA
2667	IRX.Close_mva050	50 Day MA
2668	IRX.Volume_YoY	Year over Year
2669	IRX.Volume_YoY4	4 Year over 4 Year
2670	IRX.Volume_YoY5	5 Year over 5 Year
2671	IRX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2672	IRX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
2673	IRX.Volume_SmoothDer	Derivative of Smoothed
2674	IRX.Volume_Log	Log of
2675	IRX.Volume_mva200	200 Day MA
2676	IRX.Volume_mva050	50 Day MA
2677	IRX.Adjusted_YoY	Year over Year
2680	IRX.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2682	IRX.Adjusted_SmoothDer	Derivative of Smoothed
2683	IRX.Adjusted_Log	Log of
2684	IRX.Adjusted_mva200	200 Day MA
2685	IRX.Adjusted_mva050	50 Day MA
2689	DCOILWTICO_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Crude Oil Prices: West Texas Intermediate (WTI) Cushing, Oklahoma
2692	DCOILWTICO_Log	Log of Crude Oil Prices: West Texas Intermediate (WTI) Cushing, Oklahoma
2693	DCOILWTICO_mva200	Crude Oil Prices: West Texas Intermediate (WTI) Cushing, Oklahoma 200 Day MA
2698	DCOILBRENTEU_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Crude Oil Prices: Brent - Europe
2702	DCOILBRENTEU_mva200	Crude Oil Prices: Brent - Europe 200 Day MA
2707	NEWORDER_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Manufacturers’ New Orders: Nondefense Capital Goods Excluding Aircraft
2710	NEWORDER_Log	Log of Manufacturers’ New Orders: Nondefense Capital Goods Excluding Aircraft
2711	NEWORDER_mva200	Manufacturers’ New Orders: Nondefense Capital Goods Excluding Aircraft 200 Day MA
2712	NEWORDER_mva050	Manufacturers’ New Orders: Nondefense Capital Goods Excluding Aircraft 50 Day MA
2718	ALTSALES_SmoothDer	Derivative of Smoothed Light Weight Vehicle Sales: Autos and Light Trucks
2727	ICSA_SmoothDer	Derivative of Smoothed Initial Jobless Claims
2747	GSPC.High_mva200	200 Day MA
2765	GSPC.Close_mva200	200 Day MA
2770	GSPC.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2772	GSPC.Volume_SmoothDer	Derivative of Smoothed
2783	GSPC.Adjusted_mva200	200 Day MA
2821	RLG.Volume_YoY	Year over Year
2822	RLG.Volume_YoY4	4 Year over 4 Year
2823	RLG.Volume_YoY5	5 Year over 5 Year
2824	RLG.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2825	RLG.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
2826	RLG.Volume_SmoothDer	Derivative of Smoothed
2827	RLG.Volume_Log	Log of
2828	RLG.Volume_mva200	200 Day MA
2829	RLG.Volume_mva050	50 Day MA
2842	DJI.Open_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2851	DJI.High_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2860	DJI.Low_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2869	DJI.Close_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2878	DJI.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2880	DJI.Volume_SmoothDer	Derivative of Smoothed
2883	DJI.Volume_mva050	50 Day MA
2887	DJI.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2896	STOXX50E.Open_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2900	STOXX50E.Open_mva200	200 Day MA
2905	STOXX50E.High_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2909	STOXX50E.High_mva200	200 Day MA
2914	STOXX50E.Low_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2923	STOXX50E.Close_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2927	STOXX50E.Close_mva200	200 Day MA
2934	STOXX50E.Volume_SmoothDer	Derivative of Smoothed
2935	STOXX50E.Volume_Log	Log of
2941	STOXX50E.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2945	STOXX50E.Adjusted_mva200	200 Day MA
2986	EFA.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
2988	EFA.Volume_SmoothDer	Derivative of Smoothed
2990	EFA.Volume_mva200	200 Day MA
2991	EFA.Volume_mva050	50 Day MA
3007	GDP_Log	Log of Gross Domestic Product
3008	GDP_mva200	Gross Domestic Product 200 Day MA
3009	GDP_mva050	Gross Domestic Product 50 Day MA
3015	FNDEFX_SmoothDer	Derivative of Smoothed Federal Government: Nondefense Consumption Expenditures and Gross Investment (SA, Annual Rate)
3016	FNDEFX_Log	Log of Federal Government: Nondefense Consumption Expenditures and Gross Investment (SA, Annual Rate)
3018	FNDEFX_mva050	Federal Government: Nondefense Consumption Expenditures and Gross Investment (SA, Annual Rate) 50 Day MA
3034	GDPNOW_Log	Log of Fed Atlanta GDPNow
3043	GDPC1_Log	Log of Real Gross Domestic Product
3044	GDPC1_mva200	Real Gross Domestic Product 200 Day MA
3045	GDPC1_mva050	Real Gross Domestic Product 50 Day MA
3052	GDPDEF_Log	Log of Gross Domestic Product: Implicit Price Deflator
3053	GDPDEF_mva200	Gross Domestic Product: Implicit Price Deflator 200 Day MA
3054	GDPDEF_mva050	Gross Domestic Product: Implicit Price Deflator 50 Day MA
3058	VIG.Open_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3062	VIG.Open_mva200	200 Day MA
3067	VIG.High_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3071	VIG.High_mva200	200 Day MA
3076	VIG.Low_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3085	VIG.Close_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3089	VIG.Close_mva200	200 Day MA
3094	VIG.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3096	VIG.Volume_SmoothDer	Derivative of Smoothed
3098	VIG.Volume_mva200	200 Day MA
3099	VIG.Volume_mva050	50 Day MA
3103	VIG.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3107	VIG.Adjusted_mva200	200 Day MA
3116	WLRRAL_mva200	Liabilities and Capital: Liabilities: Reverse Repurchase Agreements: Wednesday Level (NSA) 200 Day MA
3117	WLRRAL_mva050	Liabilities and Capital: Liabilities: Reverse Repurchase Agreements: Wednesday Level (NSA) 50 Day MA
3118	FEDFUNDS_YoY	Effective Federal Funds Rate Year over Year
3133	GPDI_Log	Log of Gross Private Domestic Investment
3134	GPDI_mva200	Gross Private Domestic Investment 200 Day MA
3135	GPDI_mva050	Gross Private Domestic Investment 50 Day MA
3136	W790RC1Q027SBEA_YoY	Net domestic investment: Private: Domestic busines Year over Year
3142	W790RC1Q027SBEA_Log	Log of Net domestic investment: Private: Domestic busines
3143	W790RC1Q027SBEA_mva200	Net domestic investment: Private: Domestic busines 200 Day MA
3144	W790RC1Q027SBEA_mva050	Net domestic investment: Private: Domestic busines 50 Day MA
3145	MZMV_YoY	Velocity of MZM Money Stock Year over Year
3147	MZMV_YoY5	Velocity of MZM Money Stock 5 Year over 5 Year
3151	MZMV_Log	Log of Velocity of MZM Money Stock
3152	MZMV_mva200	Velocity of MZM Money Stock 200 Day MA
3153	MZMV_mva050	Velocity of MZM Money Stock 50 Day MA
3159	M1_SmoothDer	Derivative of Smoothed M1 Money Stock
3160	M1_Log	Log of M1 Money Stock
3162	M1_mva050	M1 Money Stock 50 Day MA
3168	M2_SmoothDer	Derivative of Smoothed M2 Money Stock
3169	M2_Log	Log of M2 Money Stock
3171	M2_mva050	M2 Money Stock 50 Day MA
3175	OPHNFB_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Nonfarm Business Sector: Real Output Per Hour of All Persons
3177	OPHNFB_SmoothDer	Derivative of Smoothed Nonfarm Business Sector: Real Output Per Hour of All Persons
3178	OPHNFB_Log	Log of Nonfarm Business Sector: Real Output Per Hour of All Persons
3181	IPMAN_YoY	Industrial Production: Manufacturing (NAICS) Year over Year
3184	IPMAN_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Industrial Production: Manufacturing (NAICS)
3188	IPMAN_mva200	Industrial Production: Manufacturing (NAICS) 200 Day MA
3193	IWD.Open_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3202	IWD.High_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3206	IWD.High_mva200	200 Day MA
3211	IWD.Low_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3220	IWD.Close_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3224	IWD.Close_mva200	200 Day MA
3229	IWD.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3231	IWD.Volume_SmoothDer	Derivative of Smoothed
3233	IWD.Volume_mva200	200 Day MA
3234	IWD.Volume_mva050	50 Day MA
3238	IWD.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3242	IWD.Adjusted_mva200	200 Day MA
3247	GS5_Smooth	Savitsky-Golay Smoothed (p=3, n=365) 5-Year Treasury Constant Maturity Rate
3249	GS5_SmoothDer	Derivative of Smoothed 5-Year Treasury Constant Maturity Rate
3250	GS5_Log	Log of 5-Year Treasury Constant Maturity Rate
3251	GS5_mva200	5-Year Treasury Constant Maturity Rate 200 Day MA
3252	GS5_mva050	5-Year Treasury Constant Maturity Rate 50 Day MA
3258	PSAVERT_SmoothDer	Derivative of Smoothed Personal Saving Rate
3265	VIXCLS_Smooth	Savitsky-Golay Smoothed (p=3, n=365) CBOE Volatility Index
3267	VIXCLS_SmoothDer	Derivative of Smoothed CBOE Volatility Index
3270	VIXCLS_mva050	CBOE Volatility Index 50 Day MA
3276	VXX.Open_SmoothDer	Derivative of Smoothed
3285	VXX.High_SmoothDer	Derivative of Smoothed
3294	VXX.Low_SmoothDer	Derivative of Smoothed
3303	VXX.Close_SmoothDer	Derivative of Smoothed
3309	VXX.Volume_YoY5	5 Year over 5 Year
3310	VXX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3312	VXX.Volume_SmoothDer	Derivative of Smoothed
3313	VXX.Volume_Log	Log of
3314	VXX.Volume_mva200	200 Day MA
3315	VXX.Volume_mva050	50 Day MA
3321	VXX.Adjusted_SmoothDer	Derivative of Smoothed
3325	HOUST1F_YoY	Privately Owned Housing Starts: 1-Unit Structures Year over Year
3328	HOUST1F_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Privately Owned Housing Starts: 1-Unit Structures
3330	HOUST1F_SmoothDer	Derivative of Smoothed Privately Owned Housing Starts: 1-Unit Structures
3332	HOUST1F_mva200	Privately Owned Housing Starts: 1-Unit Structures 200 Day MA
3337	GFDEBTN_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Federal Debt: Total Public Debt
3339	GFDEBTN_SmoothDer	Derivative of Smoothed Federal Debt: Total Public Debt
3340	GFDEBTN_Log	Log of Federal Debt: Total Public Debt
3343	HOUST_YoY	Housing Starts: Total: New Privately Owned Housing Units Started Year over Year
3346	HOUST_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Housing Starts: Total: New Privately Owned Housing Units Started
3348	HOUST_SmoothDer	Derivative of Smoothed Housing Starts: Total: New Privately Owned Housing Units Started
3349	HOUST_Log	Log of Housing Starts: Total: New Privately Owned Housing Units Started
3350	HOUST_mva200	Housing Starts: Total: New Privately Owned Housing Units Started 200 Day MA
3351	HOUST_mva050	Housing Starts: Total: New Privately Owned Housing Units Started 50 Day MA
3364	UMDMNO_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Manufacturers’ New Orders: Durable Goods (NSA)
3366	UMDMNO_SmoothDer	Derivative of Smoothed Manufacturers’ New Orders: Durable Goods (NSA)
3367	UMDMNO_Log	Log of Manufacturers’ New Orders: Durable Goods (NSA)
3368	UMDMNO_mva200	Manufacturers’ New Orders: Durable Goods (NSA) 200 Day MA
3369	UMDMNO_mva050	Manufacturers’ New Orders: Durable Goods (NSA) 50 Day MA
3372	DGORDER_YoY5	Manufacturers’ New Orders: Durable Goods (SA) 5 Year over 5 Year
3377	DGORDER_mva200	Manufacturers’ New Orders: Durable Goods (SA) 200 Day MA
3385	CSUSHPINSA_Log	Log of S&P/Case-Shiller U.S. National Home Price Index (NSA)
3386	CSUSHPINSA_mva200	S&P/Case-Shiller U.S. National Home Price Index (NSA) 200 Day MA
3387	CSUSHPINSA_mva050	S&P/Case-Shiller U.S. National Home Price Index (NSA) 50 Day MA
3388	GFDEGDQ188S_YoY	Federal Debt: Total Public Debt as Percent of Gross Domestic Product Year over Year
3390	GFDEGDQ188S_YoY5	Federal Debt: Total Public Debt as Percent of Gross Domestic Product 5 Year over 5 Year
3391	GFDEGDQ188S_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Federal Debt: Total Public Debt as Percent of Gross Domestic Product
3393	GFDEGDQ188S_SmoothDer	Derivative of Smoothed Federal Debt: Total Public Debt as Percent of Gross Domestic Product
3394	GFDEGDQ188S_Log	Log of Federal Debt: Total Public Debt as Percent of Gross Domestic Product
3403	FYFSD_Log	Log of Federal Surplus or Deficit
3404	FYFSD_mva200	Federal Surplus or Deficit 200 Day MA
3405	FYFSD_mva050	Federal Surplus or Deficit 50 Day MA
3406	FYFSGDA188S_YoY	Federal Surplus or Deficit [-] as Percent of Gross Domestic Product Year over Year
3411	FYFSGDA188S_SmoothDer	Derivative of Smoothed Federal Surplus or Deficit [-] as Percent of Gross Domestic Product
3412	FYFSGDA188S_Log	Log of Federal Surplus or Deficit [-] as Percent of Gross Domestic Product
3413	FYFSGDA188S_mva200	Federal Surplus or Deficit [-] as Percent of Gross Domestic Product 200 Day MA
3414	FYFSGDA188S_mva050	Federal Surplus or Deficit [-] as Percent of Gross Domestic Product 50 Day MA
3418	GOLDAMGBD228NLBM_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Gold Fixing Price 10:30 A.M. (London time) in London Bullion Market
3463	GDX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3465	GDX.Volume_SmoothDer	Derivative of Smoothed
3467	GDX.Volume_mva200	200 Day MA
3480	XLE.Open_YoY5	5 Year over 5 Year
3481	XLE.Open_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3482	XLE.Open_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
3483	XLE.Open_SmoothDer	Derivative of Smoothed
3485	XLE.Open_mva200	200 Day MA
3486	XLE.Open_mva050	50 Day MA
3488	XLE.High_YoY4	4 Year over 4 Year
3489	XLE.High_YoY5	5 Year over 5 Year
3490	XLE.High_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3491	XLE.High_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
3492	XLE.High_SmoothDer	Derivative of Smoothed
3494	XLE.High_mva200	200 Day MA
3495	XLE.High_mva050	50 Day MA
3498	XLE.Low_YoY5	5 Year over 5 Year
3499	XLE.Low_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3500	XLE.Low_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
3501	XLE.Low_SmoothDer	Derivative of Smoothed
3503	XLE.Low_mva200	200 Day MA
3504	XLE.Low_mva050	50 Day MA
3508	XLE.Close_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3509	XLE.Close_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
3510	XLE.Close_SmoothDer	Derivative of Smoothed
3512	XLE.Close_mva200	200 Day MA
3513	XLE.Close_mva050	50 Day MA
3517	XLE.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3519	XLE.Volume_SmoothDer	Derivative of Smoothed
3521	XLE.Volume_mva200	200 Day MA
3522	XLE.Volume_mva050	50 Day MA
3526	XLE.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3527	XLE.Adjusted_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
3528	XLE.Adjusted_SmoothDer	Derivative of Smoothed
3530	XLE.Adjusted_mva200	200 Day MA
3531	XLE.Adjusted_mva050	50 Day MA
3535	GSG.Open_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3536	GSG.Open_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
3538	GSG.Open_Log	Log of
3539	GSG.Open_mva200	200 Day MA
3544	GSG.High_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3545	GSG.High_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
3547	GSG.High_Log	Log of
3548	GSG.High_mva200	200 Day MA
3553	GSG.Low_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3554	GSG.Low_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
3556	GSG.Low_Log	Log of
3557	GSG.Low_mva200	200 Day MA
3562	GSG.Close_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3563	GSG.Close_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
3565	GSG.Close_Log	Log of
3566	GSG.Close_mva200	200 Day MA
3571	GSG.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3573	GSG.Volume_SmoothDer	Derivative of Smoothed
3575	GSG.Volume_mva200	200 Day MA
3580	GSG.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
3581	GSG.Adjusted_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
3583	GSG.Adjusted_Log	Log of
3584	GSG.Adjusted_mva200	200 Day MA
3587	WALCL_YoY4	All Federal Reserve Banks: Total Assets 4 Year over 4 Year
3589	WALCL_Smooth	Savitsky-Golay Smoothed (p=3, n=365) All Federal Reserve Banks: Total Assets
3593	WALCL_mva200	All Federal Reserve Banks: Total Assets 200 Day MA
3594	WALCL_mva050	All Federal Reserve Banks: Total Assets 50 Day MA
3601	OUTMS_Log	Log of Manufacturing Sector: Real Output
3602	OUTMS_mva200	Manufacturing Sector: Real Output 200 Day MA
3603	OUTMS_mva050	Manufacturing Sector: Real Output 50 Day MA
3610	MANEMP_Log	Log of All Employees: Manufacturing
3611	MANEMP_mva200	All Employees: Manufacturing 200 Day MA
3612	MANEMP_mva050	All Employees: Manufacturing 50 Day MA
3616	PRS30006163_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Manufacturing Sector: Real Output Per Person
3619	PRS30006163_Log	Log of Manufacturing Sector: Real Output Per Person
3622	BAMLC0A3CA_YoY	ICE BofAML US Corporate A Option-Adjusted Spread Year over Year
3623	BAMLC0A3CA_YoY4	ICE BofAML US Corporate A Option-Adjusted Spread 4 Year over 4 Year
3625	BAMLC0A3CA_Smooth	Savitsky-Golay Smoothed (p=3, n=365) ICE BofAML US Corporate A Option-Adjusted Spread
3626	BAMLC0A3CA_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15) ICE BofAML US Corporate A Option-Adjusted Spread
3628	BAMLC0A3CA_Log	Log of ICE BofAML US Corporate A Option-Adjusted Spread
3629	BAMLC0A3CA_mva200	ICE BofAML US Corporate A Option-Adjusted Spread 200 Day MA
3630	BAMLC0A3CA_mva050	ICE BofAML US Corporate A Option-Adjusted Spread 50 Day MA
3634	AAA_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Moody’s Seasoned Aaa Corporate Bond Yield
3636	AAA_SmoothDer	Derivative of Smoothed Moody’s Seasoned Aaa Corporate Bond Yield
3639	AAA_mva050	Moody’s Seasoned Aaa Corporate Bond Yield 50 Day MA
3641	SOFR_YoY4	Secured Overnight Financing Rate 4 Year over 4 Year
3642	SOFR_YoY5	Secured Overnight Financing Rate 5 Year over 5 Year
3646	SOFR_Log	Log of Secured Overnight Financing Rate
3654	SOFRVOL_SmoothDer	Derivative of Smoothed Secured Overnight Financing Volume
3656	SOFRVOL_mva200	Secured Overnight Financing Volume 200 Day MA
3659	SOFR99_YoY4	Secured Overnight Financing Rate: 99th Percentile 4 Year over 4 Year
3660	SOFR99_YoY5	Secured Overnight Financing Rate: 99th Percentile 5 Year over 5 Year
3664	SOFR99_Log	Log of Secured Overnight Financing Rate: 99th Percentile
3666	SOFR99_mva050	Secured Overnight Financing Rate: 99th Percentile 50 Day MA
3682	SOFR25_Log	Log of Secured Overnight Financing Rate: 25th Percentile
3691	SOFR1_Log	Log of Secured Overnight Financing Rate: 1st Percentile
3694	OBFR_YoY	Overnight Bank Funding Rate Year over Year
3706	OBFR99_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Overnight Bank Funding Rate: 99th Percentile
3708	OBFR99_SmoothDer	Derivative of Smoothed Overnight Bank Funding Rate: 99th Percentile
3710	OBFR99_mva200	Overnight Bank Funding Rate: 99th Percentile 200 Day MA
3721	OBFR25_YoY	Overnight Bank Funding Rate: 25th Percentile Year over Year
3726	OBFR25_SmoothDer	Derivative of Smoothed Overnight Bank Funding Rate: 25th Percentile
3727	OBFR25_Log	Log of Overnight Bank Funding Rate: 25th Percentile
3736	OBFR1_Log	Log of Overnight Bank Funding Rate: 1st Percentile
3737	OBFR1_mva200	Overnight Bank Funding Rate: 1st Percentile 200 Day MA
3742	RPONTSYD_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Overnight Repurchase Agreements: Treasury Securities Purchased by the Federal Reserve in the Temporary Open Market Operations
3745	RPONTSYD_Log	Log of Overnight Repurchase Agreements: Treasury Securities Purchased by the Federal Reserve in the Temporary Open Market Operations
3748	IOER_YoY	Interest Rate on Excess Reserves Year over Year
3754	IOER_Log	Log of Interest Rate on Excess Reserves
3755	IOER_mva200	Interest Rate on Excess Reserves 200 Day MA
3756	IOER_mva050	Interest Rate on Excess Reserves 50 Day MA
3772	EXCSRESNW_Log	Log of Excess Reserves of Depository Institutions
3773	EXCSRESNW_mva200	Excess Reserves of Depository Institutions 200 Day MA
3774	EXCSRESNW_mva050	Excess Reserves of Depository Institutions 50 Day MA
3775	ECBASSETS_YoY	Central Bank Assets for Euro Area (11-19 Countries) Year over Year
3781	ECBASSETS_Log	Log of Central Bank Assets for Euro Area (11-19 Countries)
3782	ECBASSETS_mva200	Central Bank Assets for Euro Area (11-19 Countries) 200 Day MA
3783	ECBASSETS_mva050	Central Bank Assets for Euro Area (11-19 Countries) 50 Day MA
3790	EUNNGDP_Log	Log of Gross Domestic Product (Euro/ECU series) for Euro Area (19 Countries)
3791	EUNNGDP_mva200	Gross Domestic Product (Euro/ECU series) for Euro Area (19 Countries) 200 Day MA
3792	EUNNGDP_mva050	Gross Domestic Product (Euro/ECU series) for Euro Area (19 Countries) 50 Day MA
3793	CEU0600000007_YoY	Average Weekly Hours of Production and Nonsupervisory Employees: Goods-Producing Year over Year
3796	CEU0600000007_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Average Weekly Hours of Production and Nonsupervisory Employees: Goods-Producing
3798	CEU0600000007_SmoothDer	Derivative of Smoothed Average Weekly Hours of Production and Nonsupervisory Employees: Goods-Producing
3799	CEU0600000007_Log	Log of Average Weekly Hours of Production and Nonsupervisory Employees: Goods-Producing
3800	CEU0600000007_mva200	Average Weekly Hours of Production and Nonsupervisory Employees: Goods-Producing 200 Day MA
3801	CEU0600000007_mva050	Average Weekly Hours of Production and Nonsupervisory Employees: Goods-Producing 50 Day MA
3802	USD1MTD156N_YoY	1-Month London Interbank Offered Rate (LIBOR), based on U.S. Dollar Year over Year
3805	USD1MTD156N_Smooth	Savitsky-Golay Smoothed (p=3, n=365) 1-Month London Interbank Offered Rate (LIBOR), based on U.S. Dollar
3806	USD1MTD156N_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15) 1-Month London Interbank Offered Rate (LIBOR), based on U.S. Dollar
3807	USD1MTD156N_SmoothDer	Derivative of Smoothed 1-Month London Interbank Offered Rate (LIBOR), based on U.S. Dollar
3814	CURRENCY_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Currency Component of M1 (Seasonally Adjusted)
3816	CURRENCY_SmoothDer	Derivative of Smoothed Currency Component of M1 (Seasonally Adjusted)
3817	CURRENCY_Log	Log of Currency Component of M1 (Seasonally Adjusted)
3818	CURRENCY_mva200	Currency Component of M1 (Seasonally Adjusted) 200 Day MA
3819	CURRENCY_mva050	Currency Component of M1 (Seasonally Adjusted) 50 Day MA
3823	WCURRNS_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Currency Component of M1
3827	WCURRNS_mva200	Currency Component of M1 200 Day MA
3828	WCURRNS_mva050	Currency Component of M1 50 Day MA
3832	BOGMBASE_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Monetary Base; Total
3835	BOGMBASE_Log	Log of Monetary Base; Total
3836	BOGMBASE_mva200	Monetary Base; Total 200 Day MA
3837	BOGMBASE_mva050	Monetary Base; Total 50 Day MA
3841	PRS88003193_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Nonfinancial Corporations Sector: Unit Profits
3844	PRS88003193_Log	Log of Nonfinancial Corporations Sector: Unit Profits
3845	PRS88003193_mva200	Nonfinancial Corporations Sector: Unit Profits 200 Day MA
3846	PRS88003193_mva050	Nonfinancial Corporations Sector: Unit Profits 50 Day MA
3854	PPIACO_mva200	Producer Price Index for All Commodities 200 Day MA
3863	PCUOMFGOMFG_mva200	Producer Price Index by Industry: Total Manufacturing Industries 200 Day MA
3877	POPTHM_Log	Log of Population (U.S.)
3878	POPTHM_Log	Log of Population (U.S.)
3879	POPTHM_mva200	Population (U.S.) 200 Day MA
3880	POPTHM_mva200	Population (U.S.) 200 Day MA
3881	POPTHM_mva050	Population (U.S.) 50 Day MA
3882	POPTHM_mva050	Population (U.S.) 50 Day MA
3895	POPTHM.1_Log	Log of
3896	POPTHM.1_Log	Log of
3897	POPTHM.1_mva200	200 Day MA
3898	POPTHM.1_mva200	200 Day MA
3899	POPTHM.1_mva050	50 Day MA
3900	POPTHM.1_mva050	50 Day MA
3904	CLF16OV_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Civilian Labor Force Level, SA
3907	CLF16OV_Log	Log of Civilian Labor Force Level, SA
3908	CLF16OV_mva200	Civilian Labor Force Level, SA 200 Day MA
3909	CLF16OV_mva050	Civilian Labor Force Level, SA 50 Day MA
3924	LNU03000000_SmoothDer	Derivative of Smoothed Unemployment Level (NSA)
3940	RSAFS_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Advance Retail Sales: Retail and Food Services
3944	RSAFS_mva200	Advance Retail Sales: Retail and Food Services 200 Day MA
3949	FRGSHPUSM649NCIS_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Cass Freight Index: Shipments
3961	BOPGTB_Log	Log of Trade Balance: Goods, Balance of Payments Basis (SA)
3978	A065RC1A027NBEA_SmoothDer	Derivative of Smoothed Personal income (NSA)
3979	A065RC1A027NBEA_Log	Log of Personal income (NSA)
3980	A065RC1A027NBEA_mva200	Personal income (NSA) 200 Day MA
3981	A065RC1A027NBEA_mva050	Personal income (NSA) 50 Day MA
3987	PI_SmoothDer	Derivative of Smoothed Personal income (SA)
3988	PI_Log	Log of Personal income (SA)
3990	PI_mva050	Personal income (SA) 50 Day MA
3998	PCE_mva200	Personal Consumption Expenditures (SA) 200 Day MA
4003	A053RC1Q027SBEA_Smooth	Savitsky-Golay Smoothed (p=3, n=365) National income: Corporate profits before tax (without IVA and CCAdj)
4006	A053RC1Q027SBEA_Log	Log of National income: Corporate profits before tax (without IVA and CCAdj)
4007	A053RC1Q027SBEA_mva200	National income: Corporate profits before tax (without IVA and CCAdj) 200 Day MA
4008	A053RC1Q027SBEA_mva050	National income: Corporate profits before tax (without IVA and CCAdj) 50 Day MA
4012	CPROFIT_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Corporate Profits with Inventory Valuation Adjustment (IVA) and Capital Consumption Adjustment (CCAdj)
4015	CPROFIT_Log	Log of Corporate Profits with Inventory Valuation Adjustment (IVA) and Capital Consumption Adjustment (CCAdj)
4016	CPROFIT_mva200	Corporate Profits with Inventory Valuation Adjustment (IVA) and Capital Consumption Adjustment (CCAdj) 200 Day MA
4017	CPROFIT_mva050	Corporate Profits with Inventory Valuation Adjustment (IVA) and Capital Consumption Adjustment (CCAdj) 50 Day MA
4034	SPY.High_mva200	200 Day MA
4052	SPY.Close_mva200	200 Day MA
4057	SPY.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4059	SPY.Volume_SmoothDer	Derivative of Smoothed
4061	SPY.Volume_mva200	200 Day MA
4062	SPY.Volume_mva050	50 Day MA
4070	SPY.Adjusted_mva200	200 Day MA
4084	MDY.High_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4086	MDY.High_SmoothDer	Derivative of Smoothed
4111	MDY.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4113	MDY.Volume_SmoothDer	Derivative of Smoothed
4115	MDY.Volume_mva200	200 Day MA
4116	MDY.Volume_mva050	50 Day MA
4120	MDY.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4122	MDY.Adjusted_SmoothDer	Derivative of Smoothed
4129	EES.Open_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4131	EES.Open_SmoothDer	Derivative of Smoothed
4138	EES.High_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4140	EES.High_SmoothDer	Derivative of Smoothed
4147	EES.Low_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4156	EES.Close_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4158	EES.Close_SmoothDer	Derivative of Smoothed
4165	EES.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4167	EES.Volume_SmoothDer	Derivative of Smoothed
4168	EES.Volume_Log	Log of
4170	EES.Volume_mva050	50 Day MA
4174	EES.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4176	EES.Adjusted_SmoothDer	Derivative of Smoothed
4185	IJR.Open_SmoothDer	Derivative of Smoothed
4194	IJR.High_SmoothDer	Derivative of Smoothed
4203	IJR.Low_SmoothDer	Derivative of Smoothed
4212	IJR.Close_SmoothDer	Derivative of Smoothed
4219	IJR.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4221	IJR.Volume_SmoothDer	Derivative of Smoothed
4224	IJR.Volume_mva050	50 Day MA
4230	IJR.Adjusted_SmoothDer	Derivative of Smoothed
4270	VGSTX.Volume_YoY	Year over Year
4271	VGSTX.Volume_YoY4	4 Year over 4 Year
4272	VGSTX.Volume_YoY5	5 Year over 5 Year
4273	VGSTX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4274	VGSTX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
4275	VGSTX.Volume_SmoothDer	Derivative of Smoothed
4276	VGSTX.Volume_Log	Log of
4277	VGSTX.Volume_mva200	200 Day MA
4278	VGSTX.Volume_mva050	50 Day MA
4295	VFINX.Open_mva200	200 Day MA
4304	VFINX.High_mva200	200 Day MA
4313	VFINX.Low_mva200	200 Day MA
4322	VFINX.Close_mva200	200 Day MA
4324	VFINX.Volume_YoY	Year over Year
4325	VFINX.Volume_YoY4	4 Year over 4 Year
4326	VFINX.Volume_YoY5	5 Year over 5 Year
4327	VFINX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4328	VFINX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
4329	VFINX.Volume_SmoothDer	Derivative of Smoothed
4330	VFINX.Volume_Log	Log of
4331	VFINX.Volume_mva200	200 Day MA
4332	VFINX.Volume_mva050	50 Day MA
4340	VFINX.Adjusted_mva200	200 Day MA
4345	VOE.Open_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4349	VOE.Open_mva200	200 Day MA
4354	VOE.High_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4358	VOE.High_mva200	200 Day MA
4363	VOE.Low_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4367	VOE.Low_mva200	200 Day MA
4372	VOE.Close_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4376	VOE.Close_mva200	200 Day MA
4381	VOE.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4383	VOE.Volume_SmoothDer	Derivative of Smoothed
4386	VOE.Volume_mva050	50 Day MA
4390	VOE.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4394	VOE.Adjusted_mva200	200 Day MA
4435	VOT.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4437	VOT.Volume_SmoothDer	Derivative of Smoothed
4439	VOT.Volume_mva200	200 Day MA
4440	VOT.Volume_mva050	50 Day MA
4486	TMFGX.Volume_YoY	Year over Year
4487	TMFGX.Volume_YoY4	4 Year over 4 Year
4488	TMFGX.Volume_YoY5	5 Year over 5 Year
4489	TMFGX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4490	TMFGX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
4491	TMFGX.Volume_SmoothDer	Derivative of Smoothed
4492	TMFGX.Volume_Log	Log of
4493	TMFGX.Volume_mva200	200 Day MA
4494	TMFGX.Volume_mva050	50 Day MA
4509	IWM.Open_SmoothDer	Derivative of Smoothed
4518	IWM.High_SmoothDer	Derivative of Smoothed
4536	IWM.Close_SmoothDer	Derivative of Smoothed
4543	IWM.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4545	IWM.Volume_SmoothDer	Derivative of Smoothed
4547	IWM.Volume_mva200	200 Day MA
4548	IWM.Volume_mva050	50 Day MA
4554	IWM.Adjusted_SmoothDer	Derivative of Smoothed
4597	ONEQ.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4599	ONEQ.Volume_SmoothDer	Derivative of Smoothed
4602	ONEQ.Volume_mva050	50 Day MA
4648	HAINX.Volume_YoY	Year over Year
4649	HAINX.Volume_YoY4	4 Year over 4 Year
4650	HAINX.Volume_YoY5	5 Year over 5 Year
4651	HAINX.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4652	HAINX.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
4653	HAINX.Volume_SmoothDer	Derivative of Smoothed
4654	HAINX.Volume_Log	Log of
4655	HAINX.Volume_mva200	200 Day MA
4656	HAINX.Volume_mva050	50 Day MA
4705	VEU.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4707	VEU.Volume_SmoothDer	Derivative of Smoothed
4709	VEU.Volume_mva200	200 Day MA
4710	VEU.Volume_mva050	50 Day MA
4725	BIL.Open_SmoothDer	Derivative of Smoothed
4734	BIL.High_SmoothDer	Derivative of Smoothed
4743	BIL.Low_SmoothDer	Derivative of Smoothed
4752	BIL.Close_SmoothDer	Derivative of Smoothed
4758	BIL.Volume_YoY5	5 Year over 5 Year
4759	BIL.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4761	BIL.Volume_SmoothDer	Derivative of Smoothed
4763	BIL.Volume_mva200	200 Day MA
4764	BIL.Volume_mva050	50 Day MA
4770	BIL.Adjusted_SmoothDer	Derivative of Smoothed
4786	IVOO.High_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4813	IVOO.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4815	IVOO.Volume_SmoothDer	Derivative of Smoothed
4816	IVOO.Volume_Log	Log of
4822	IVOO.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4867	VO.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4869	VO.Volume_SmoothDer	Derivative of Smoothed
4870	VO.Volume_Log	Log of
4871	VO.Volume_mva200	200 Day MA
4872	VO.Volume_mva050	50 Day MA
4894	CZA.High_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4912	CZA.Close_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4919	CZA.Volume_YoY4	4 Year over 4 Year
4921	CZA.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4922	CZA.Volume_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
4923	CZA.Volume_SmoothDer	Derivative of Smoothed
4924	CZA.Volume_Log	Log of
4926	CZA.Volume_mva050	50 Day MA
4930	CZA.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4939	VYM.Open_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4941	VYM.Open_SmoothDer	Derivative of Smoothed
4943	VYM.Open_mva200	200 Day MA
4948	VYM.High_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4950	VYM.High_SmoothDer	Derivative of Smoothed
4952	VYM.High_mva200	200 Day MA
4953	VYM.High_mva050	50 Day MA
4957	VYM.Low_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4959	VYM.Low_SmoothDer	Derivative of Smoothed
4961	VYM.Low_mva200	200 Day MA
4966	VYM.Close_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4968	VYM.Close_SmoothDer	Derivative of Smoothed
4970	VYM.Close_mva200	200 Day MA
4971	VYM.Close_mva050	50 Day MA
4975	VYM.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4977	VYM.Volume_SmoothDer	Derivative of Smoothed
4980	VYM.Volume_mva050	50 Day MA
4984	VYM.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
4986	VYM.Adjusted_SmoothDer	Derivative of Smoothed
4988	VYM.Adjusted_mva200	200 Day MA
4989	VYM.Adjusted_mva050	50 Day MA
5029	ACWI.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5031	ACWI.Volume_SmoothDer	Derivative of Smoothed
5033	ACWI.Volume_mva200	200 Day MA
5034	ACWI.Volume_mva050	50 Day MA
5049	SLY.Open_SmoothDer	Derivative of Smoothed
5058	SLY.High_SmoothDer	Derivative of Smoothed
5067	SLY.Low_SmoothDer	Derivative of Smoothed
5076	SLY.Close_SmoothDer	Derivative of Smoothed
5083	SLY.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5085	SLY.Volume_SmoothDer	Derivative of Smoothed
5086	SLY.Volume_Log	Log of
5088	SLY.Volume_mva050	50 Day MA
5094	SLY.Adjusted_SmoothDer	Derivative of Smoothed
5137	QQQ.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5139	QQQ.Volume_SmoothDer	Derivative of Smoothed
5141	QQQ.Volume_mva200	200 Day MA
5142	QQQ.Volume_mva050	50 Day MA
5191	HYMB.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5193	HYMB.Volume_SmoothDer	Derivative of Smoothed
5194	HYMB.Volume_Log	Log of
5195	HYMB.Volume_mva200	200 Day MA
5196	HYMB.Volume_mva050	50 Day MA
5212	GOLD.Open_Log	Log of
5247	GOLD.Volume_SmoothDer	Derivative of Smoothed
5248	GOLD.Volume_Log	Log of
5263	BKR.Open_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5265	BKR.Open_SmoothDer	Derivative of Smoothed
5266	BKR.Open_Log	Log of
5267	BKR.Open_mva200	200 Day MA
5268	BKR.Open_mva050	50 Day MA
5272	BKR.High_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5274	BKR.High_SmoothDer	Derivative of Smoothed
5276	BKR.High_mva200	200 Day MA
5277	BKR.High_mva050	50 Day MA
5281	BKR.Low_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5282	BKR.Low_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
5283	BKR.Low_SmoothDer	Derivative of Smoothed
5285	BKR.Low_mva200	200 Day MA
5286	BKR.Low_mva050	50 Day MA
5290	BKR.Close_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5292	BKR.Close_SmoothDer	Derivative of Smoothed
5294	BKR.Close_mva200	200 Day MA
5295	BKR.Close_mva050	50 Day MA
5299	BKR.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5302	BKR.Volume_Log	Log of
5308	BKR.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5310	BKR.Adjusted_SmoothDer	Derivative of Smoothed
5312	BKR.Adjusted_mva200	200 Day MA
5313	BKR.Adjusted_mva050	50 Day MA
5317	SLB.Open_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5318	SLB.Open_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
5319	SLB.Open_SmoothDer	Derivative of Smoothed
5322	SLB.Open_mva050	50 Day MA
5326	SLB.High_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5327	SLB.High_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
5328	SLB.High_SmoothDer	Derivative of Smoothed
5331	SLB.High_mva050	50 Day MA
5334	SLB.Low_YoY5	5 Year over 5 Year
5335	SLB.Low_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5336	SLB.Low_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
5337	SLB.Low_SmoothDer	Derivative of Smoothed
5338	SLB.Low_Log	Log of
5340	SLB.Low_mva050	50 Day MA
5344	SLB.Close_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5345	SLB.Close_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
5346	SLB.Close_SmoothDer	Derivative of Smoothed
5349	SLB.Close_mva050	50 Day MA
5353	SLB.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5355	SLB.Volume_SmoothDer	Derivative of Smoothed
5358	SLB.Volume_mva050	50 Day MA
5362	SLB.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5363	SLB.Adjusted_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
5364	SLB.Adjusted_SmoothDer	Derivative of Smoothed
5366	SLB.Adjusted_mva200	200 Day MA
5367	SLB.Adjusted_mva050	50 Day MA
5371	HAL.Open_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5372	HAL.Open_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
5373	HAL.Open_SmoothDer	Derivative of Smoothed
5374	HAL.Open_Log	Log of
5375	HAL.Open_mva200	200 Day MA
5376	HAL.Open_mva050	50 Day MA
5379	HAL.High_YoY5	5 Year over 5 Year
5380	HAL.High_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5381	HAL.High_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
5382	HAL.High_SmoothDer	Derivative of Smoothed
5384	HAL.High_mva200	200 Day MA
5385	HAL.High_mva050	50 Day MA
5389	HAL.Low_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5390	HAL.Low_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
5391	HAL.Low_SmoothDer	Derivative of Smoothed
5392	HAL.Low_Log	Log of
5393	HAL.Low_mva200	200 Day MA
5394	HAL.Low_mva050	50 Day MA
5398	HAL.Close_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5399	HAL.Close_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
5400	HAL.Close_SmoothDer	Derivative of Smoothed
5401	HAL.Close_Log	Log of
5402	HAL.Close_mva200	200 Day MA
5403	HAL.Close_mva050	50 Day MA
5407	HAL.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5409	HAL.Volume_SmoothDer	Derivative of Smoothed
5410	HAL.Volume_Log	Log of
5412	HAL.Volume_mva050	50 Day MA
5416	HAL.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5417	HAL.Adjusted_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15)
5418	HAL.Adjusted_SmoothDer	Derivative of Smoothed
5419	HAL.Adjusted_Log	Log of
5420	HAL.Adjusted_mva200	200 Day MA
5421	HAL.Adjusted_mva050	50 Day MA
5428	IP.Open_Log	Log of
5461	IP.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5463	IP.Volume_SmoothDer	Derivative of Smoothed
5481	PKG.Open_SmoothDer	Derivative of Smoothed
5490	PKG.High_SmoothDer	Derivative of Smoothed
5499	PKG.Low_SmoothDer	Derivative of Smoothed
5508	PKG.Close_SmoothDer	Derivative of Smoothed
5515	PKG.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5517	PKG.Volume_SmoothDer	Derivative of Smoothed
5519	PKG.Volume_mva200	200 Day MA
5526	PKG.Adjusted_SmoothDer	Derivative of Smoothed
5533	UPS.Open_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5542	UPS.High_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5551	UPS.Low_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5560	UPS.Close_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5571	UPS.Volume_SmoothDer	Derivative of Smoothed
5578	UPS.Adjusted_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5643	T.Open_SmoothDer	Derivative of Smoothed
5644	T.Open_Log	Log of
5652	T.High_SmoothDer	Derivative of Smoothed
5670	T.Close_SmoothDer	Derivative of Smoothed
5677	T.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5679	T.Volume_SmoothDer	Derivative of Smoothed
5681	T.Volume_mva200	200 Day MA
5682	T.Volume_mva050	50 Day MA
5688	T.Adjusted_SmoothDer	Derivative of Smoothed
5719	VZ.Close_YoY	Year over Year
5731	VZ.Volume_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
5733	VZ.Volume_SmoothDer	Derivative of Smoothed
5735	VZ.Volume_mva200	200 Day MA
5736	VZ.Volume_mva050	50 Day MA
5737	VZ.Adjusted_YoY	Year over Year
5751	ISMMANPMI_SmoothDer	Derivative of Smoothed Institute of Supply Managment PMI Composite Index
5760	MULTPLSP500PERATIOMONTH_SmoothDer	Derivative of Smoothed S&P 500 TTM P/E
5770	MULTPLSP500SALESQUARTER_Log	Log of S&P 500 TTM Sales (Not Inflation Adjusted)
5771	MULTPLSP500SALESQUARTER_mva200	S&P 500 TTM Sales (Not Inflation Adjusted) 200 Day MA
5772	MULTPLSP500SALESQUARTER_mva050	S&P 500 TTM Sales (Not Inflation Adjusted) 50 Day MA
5773	MULTPLSP500DIVYIELDMONTH_YoY	S&P 500 Dividend Yield by Month Year over Year
5774	MULTPLSP500DIVYIELDMONTH_YoY4	S&P 500 Dividend Yield by Month 4 Year over 4 Year
5778	MULTPLSP500DIVYIELDMONTH_SmoothDer	Derivative of Smoothed S&P 500 Dividend Yield by Month
5782	MULTPLSP500DIVMONTH_YoY	S&P 500 Dividend by Month (Inflation Adjusted) Year over Year
5787	MULTPLSP500DIVMONTH_SmoothDer	Derivative of Smoothed S&P 500 Dividend by Month (Inflation Adjusted)
5788	MULTPLSP500DIVMONTH_Log	Log of S&P 500 Dividend by Month (Inflation Adjusted)
5790	MULTPLSP500DIVMONTH_mva050	S&P 500 Dividend by Month (Inflation Adjusted) 50 Day MA
5794	CHRISCMEHG1_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Copper Futures, Continuous Contract #1 (HG1) (Front Month)
5797	CHRISCMEHG1_Log	Log of Copper Futures, Continuous Contract #1 (HG1) (Front Month)
5800	WWDIWLDISAIRGOODMTK1_YoY	Air transport, freight Year over Year
5806	WWDIWLDISAIRGOODMTK1_Log	Log of Air transport, freight
5807	WWDIWLDISAIRGOODMTK1_mva200	Air transport, freight 200 Day MA
5808	WWDIWLDISAIRGOODMTK1_mva050	Air transport, freight 50 Day MA
5815	BKRTotal_Log	Log of Total Rig Count
5816	BKRTotal_mva200	Total Rig Count 200 Day MA
5817	BKRTotal_mva050	Total Rig Count 50 Day MA
5824	BKRGas_Log	Log of Gas Rig Count
5825	BKRGas_mva200	Gas Rig Count 200 Day MA
5826	BKRGas_mva050	Gas Rig Count 50 Day MA
5833	BKROil_Log	Log of Oil Rig Count
5834	BKROil_mva200	Oil Rig Count 200 Day MA
5835	BKROil_mva050	Oil Rig Count 50 Day MA
5836	FARMINCOME_YoY	Net Farm Income Year over Year
5842	FARMINCOME_Log	Log of Net Farm Income
5843	FARMINCOME_mva200	Net Farm Income 200 Day MA
5844	FARMINCOME_mva050	Net Farm Income 50 Day MA
5848	OPEARNINGSPERSHARE_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Operating Earnings per Share
5851	OPEARNINGSPERSHARE_Log	Log of Operating Earnings per Share
5852	OPEARNINGSPERSHARE_mva200	Operating Earnings per Share 200 Day MA
5853	OPEARNINGSPERSHARE_mva050	Operating Earnings per Share 50 Day MA
5857	AREARNINGSPERSHARE_Smooth	Savitsky-Golay Smoothed (p=3, n=365) As-Reported Earnings per Share
5860	AREARNINGSPERSHARE_Log	Log of As-Reported Earnings per Share
5861	AREARNINGSPERSHARE_mva200	As-Reported Earnings per Share 200 Day MA
5862	AREARNINGSPERSHARE_mva050	As-Reported Earnings per Share 50 Day MA
5866	CASHDIVIDENDSPERSHR_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Cash Dividends per Share
5868	CASHDIVIDENDSPERSHR_SmoothDer	Derivative of Smoothed Cash Dividends per Share
5869	CASHDIVIDENDSPERSHR_Log	Log of Cash Dividends per Share
5870	CASHDIVIDENDSPERSHR_mva200	Cash Dividends per Share 200 Day MA
5871	CASHDIVIDENDSPERSHR_mva050	Cash Dividends per Share 50 Day MA
5877	SALESPERSHR_SmoothDer	Derivative of Smoothed Sales per Share
5878	SALESPERSHR_Log	Log of Sales per Share
5880	SALESPERSHR_mva050	Sales per Share 50 Day MA
5884	BOOKVALPERSHR_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Book value per Share
5887	BOOKVALPERSHR_Log	Log of Book value per Share
5888	BOOKVALPERSHR_mva200	Book value per Share 200 Day MA
5889	BOOKVALPERSHR_mva050	Book value per Share 50 Day MA
5895	CAPEXPERSHR_SmoothDer	Derivative of Smoothed Cap ex per Share
5896	CAPEXPERSHR_Log	Log of Cap ex per Share
5898	CAPEXPERSHR_mva050	Cap ex per Share 50 Day MA
5902	PRICE_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Price
5904	PRICE_SmoothDer	Derivative of Smoothed Price
5905	PRICE_Log	Log of Price
5906	PRICE_mva200	Price 200 Day MA
5907	PRICE_mva050	Price 50 Day MA
5911	OPEARNINGSTTM_Smooth	Savitsky-Golay Smoothed (p=3, n=365) TTM Operating Earnings
5914	OPEARNINGSTTM_Log	Log of TTM Operating Earnings
5915	OPEARNINGSTTM_mva200	TTM Operating Earnings 200 Day MA
5916	OPEARNINGSTTM_mva050	TTM Operating Earnings 50 Day MA
5920	AREARNINGSTTM_Smooth	Savitsky-Golay Smoothed (p=3, n=365) TTM Reported Earnings
5923	AREARNINGSTTM_Log	Log of TTM Reported Earnings
5924	AREARNINGSTTM_mva200	TTM Reported Earnings 200 Day MA
5925	AREARNINGSTTM_mva050	TTM Reported Earnings 50 Day MA
5933	FINRAMarginDebt_mva200	Margin Debt 200 Day MA
5936	FINRAFreeCreditMargin_YoY4	Free Credit Balances in Customers’ Securities Margin Accounts 4 Year over 4 Year
5938	FINRAFreeCreditMargin_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Free Credit Balances in Customers’ Securities Margin Accounts
5940	FINRAFreeCreditMargin_SmoothDer	Derivative of Smoothed Free Credit Balances in Customers’ Securities Margin Accounts
5941	FINRAFreeCreditMargin_Log	Log of Free Credit Balances in Customers’ Securities Margin Accounts
5944	OCCEquityVolume_YoY	Equity Options Volume Year over Year
5950	OCCEquityVolume_Log	Log of Equity Options Volume
5951	OCCEquityVolume_mva200	Equity Options Volume 200 Day MA
5952	OCCEquityVolume_mva050	Equity Options Volume 50 Day MA
5953	OCCNonEquityVolume_YoY	Non-Equity Options Volume Year over Year
5959	OCCNonEquityVolume_Log	Log of Non-Equity Options Volume
5960	OCCNonEquityVolume_mva200	Non-Equity Options Volume 200 Day MA
5961	OCCNonEquityVolume_mva050	Non-Equity Options Volume 50 Day MA
5972	BUSLOANS.minus.BUSLOANSNSA_YoY4	Business Loans (Montlhy) SA - NSA 4 Year over 4 Year
5973	BUSLOANS.minus.BUSLOANSNSA_YoY5	Business Loans (Montlhy) SA - NSA 5 Year over 5 Year
5977	BUSLOANS.minus.BUSLOANSNSA_Log	Log of Business Loans (Montlhy) SA - NSA
5978	BUSLOANS.minus.BUSLOANSNSA_mva200	Business Loans (Montlhy) SA - NSA 200 Day MA
5981	BUSLOANS.minus.BUSLOANSNSA.by.GDP_YoY4	Business Loans (Montlhy) SA - NSA divided by GDP 4 Year over 4 Year
5982	BUSLOANS.minus.BUSLOANSNSA.by.GDP_YoY5	Business Loans (Montlhy) SA - NSA divided by GDP 5 Year over 5 Year
5986	BUSLOANS.minus.BUSLOANSNSA.by.GDP_Log	Log of Business Loans (Montlhy) SA - NSA divided by GDP
5987	BUSLOANS.minus.BUSLOANSNSA.by.GDP_mva200	Business Loans (Montlhy) SA - NSA divided by GDP 200 Day MA
5989	BUSLOANS.by.GDP_YoY	Business Loans Normalized by GDP Year over Year
5990	BUSLOANS.by.GDP_YoY4	Business Loans Normalized by GDP 4 Year over 4 Year
5991	BUSLOANS.by.GDP_YoY5	Business Loans Normalized by GDP 5 Year over 5 Year
5992	BUSLOANS.by.GDP_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Business Loans Normalized by GDP
5994	BUSLOANS.by.GDP_SmoothDer	Derivative of Smoothed Business Loans Normalized by GDP
5995	BUSLOANS.by.GDP_Log	Log of Business Loans Normalized by GDP
6001	BUSLOANS.INTEREST_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Business Loans (Monthly, SA) Adjusted Interest Burdens
6002	BUSLOANS.INTEREST_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15) Business Loans (Monthly, SA) Adjusted Interest Burdens
6003	BUSLOANS.INTEREST_SmoothDer	Derivative of Smoothed Business Loans (Monthly, SA) Adjusted Interest Burdens
6006	BUSLOANS.INTEREST_mva050	Business Loans (Monthly, SA) Adjusted Interest Burdens 50 Day MA
6010	BUSLOANS.INTEREST.by.GDP_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Business Loans (Monthly, SA) Adjusted Interest Burden Divided by GDP
6011	BUSLOANS.INTEREST.by.GDP_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15) Business Loans (Monthly, SA) Adjusted Interest Burden Divided by GDP
6012	BUSLOANS.INTEREST.by.GDP_SmoothDer	Derivative of Smoothed Business Loans (Monthly, SA) Adjusted Interest Burden Divided by GDP
6015	BUSLOANS.INTEREST.by.GDP_mva050	Business Loans (Monthly, SA) Adjusted Interest Burden Divided by GDP 50 Day MA
6017	BUSLOANSNSA.by.GDP_YoY4	Business Loans Normalized by GDP 4 Year over 4 Year
6019	BUSLOANSNSA.by.GDP_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Business Loans Normalized by GDP
6021	BUSLOANSNSA.by.GDP_SmoothDer	Derivative of Smoothed Business Loans Normalized by GDP
6022	BUSLOANSNSA.by.GDP_Log	Log of Business Loans Normalized by GDP
6026	TOTCI.by.GDP_YoY4	Business Loans (Weekly, SA) Normalized by GDP 4 Year over 4 Year
6028	TOTCI.by.GDP_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Business Loans (Weekly, SA) Normalized by GDP
6030	TOTCI.by.GDP_SmoothDer	Derivative of Smoothed Business Loans (Weekly, SA) Normalized by GDP
6037	TOTCINSA.by.GDP_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Business Loans (Weekly, NSA) Normalized by GDP
6039	TOTCINSA.by.GDP_SmoothDer	Derivative of Smoothed Business Loans (Weekly, NSA) Normalized by GDP
6046	TOTCINSA.INTEREST_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Business Loans (Weekly, NSA) Adjusted Interest Burdens
6047	TOTCINSA.INTEREST_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15) Business Loans (Weekly, NSA) Adjusted Interest Burdens
6048	TOTCINSA.INTEREST_SmoothDer	Derivative of Smoothed Business Loans (Weekly, NSA) Adjusted Interest Burdens
6051	TOTCINSA.INTEREST_mva050	Business Loans (Weekly, NSA) Adjusted Interest Burdens 50 Day MA
6055	TOTCINSA.INTEREST.by.GDP_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Business Loans (weekly, NSA) Adjusted Interest Burden Divided by GDP
6056	TOTCINSA.INTEREST.by.GDP_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15) Business Loans (weekly, NSA) Adjusted Interest Burden Divided by GDP
6057	TOTCINSA.INTEREST.by.GDP_SmoothDer	Derivative of Smoothed Business Loans (weekly, NSA) Adjusted Interest Burden Divided by GDP
6060	TOTCINSA.INTEREST.by.GDP_mva050	Business Loans (weekly, NSA) Adjusted Interest Burden Divided by GDP 50 Day MA
6061	W875RX1.by.GDP_YoY	Real Personal Income Normalized by GDP Year over Year
6066	W875RX1.by.GDP_SmoothDer	Derivative of Smoothed Real Personal Income Normalized by GDP
6075	A065RC1A027NBEA.by.GDP_SmoothDer	Derivative of Smoothed Personal Income (NSA) Normalized by GDP
6084	PI.by.GDP_SmoothDer	Derivative of Smoothed Personal Income (SA) Normalized by GDP
6106	CONSUMERNSA.by.GDP_YoY	Consumer Loans Not Seasonally Adjusted divided by GDP Year over Year
6107	CONSUMERNSA.by.GDP_YoY4	Consumer Loans Not Seasonally Adjusted divided by GDP 4 Year over 4 Year
6108	CONSUMERNSA.by.GDP_YoY5	Consumer Loans Not Seasonally Adjusted divided by GDP 5 Year over 5 Year
6109	CONSUMERNSA.by.GDP_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Consumer Loans Not Seasonally Adjusted divided by GDP
6111	CONSUMERNSA.by.GDP_SmoothDer	Derivative of Smoothed Consumer Loans Not Seasonally Adjusted divided by GDP
6112	CONSUMERNSA.by.GDP_Log	Log of Consumer Loans Not Seasonally Adjusted divided by GDP
6113	CONSUMERNSA.by.GDP_mva200	Consumer Loans Not Seasonally Adjusted divided by GDP 200 Day MA
6114	CONSUMERNSA.by.GDP_mva050	Consumer Loans Not Seasonally Adjusted divided by GDP 50 Day MA
6115	RREACBM027NBOG.by.GDP_YoY	Residental Real Estate Loans (Monthly, NSA) divided by GDP Year over Year
6116	RREACBM027NBOG.by.GDP_YoY4	Residental Real Estate Loans (Monthly, NSA) divided by GDP 4 Year over 4 Year
6117	RREACBM027NBOG.by.GDP_YoY5	Residental Real Estate Loans (Monthly, NSA) divided by GDP 5 Year over 5 Year
6118	RREACBM027NBOG.by.GDP_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Residental Real Estate Loans (Monthly, NSA) divided by GDP
6120	RREACBM027NBOG.by.GDP_SmoothDer	Derivative of Smoothed Residental Real Estate Loans (Monthly, NSA) divided by GDP
6124	RREACBM027SBOG.by.GDP_YoY	Residental Real Estate Loans (Monthly, SA) divided by GDP Year over Year
6125	RREACBM027SBOG.by.GDP_YoY4	Residental Real Estate Loans (Monthly, SA) divided by GDP 4 Year over 4 Year
6126	RREACBM027SBOG.by.GDP_YoY5	Residental Real Estate Loans (Monthly, SA) divided by GDP 5 Year over 5 Year
6127	RREACBM027SBOG.by.GDP_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Residental Real Estate Loans (Monthly, SA) divided by GDP
6129	RREACBM027SBOG.by.GDP_SmoothDer	Derivative of Smoothed Residental Real Estate Loans (Monthly, SA) divided by GDP
6133	RREACBW027SBOG.by.GDP_YoY	Residental Real Estate Loans (Weekly, SA) divided by GDP Year over Year
6135	RREACBW027SBOG.by.GDP_YoY5	Residental Real Estate Loans (Weekly, SA) divided by GDP 5 Year over 5 Year
6136	RREACBW027SBOG.by.GDP_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Residental Real Estate Loans (Weekly, SA) divided by GDP
6138	RREACBW027SBOG.by.GDP_SmoothDer	Derivative of Smoothed Residental Real Estate Loans (Weekly, SA) divided by GDP
6142	RREACBW027NBOG.by.GDP_YoY	Residental Real Estate Loans (Weekly, NSA) divided by GDP Year over Year
6145	RREACBW027NBOG.by.GDP_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Residental Real Estate Loans (Weekly, NSA) divided by GDP
6147	RREACBW027NBOG.by.GDP_SmoothDer	Derivative of Smoothed Residental Real Estate Loans (Weekly, NSA) divided by GDP
6154	UMDMNO.by.GDP_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Durable Goods (Monthly, NSA) divided by GDP
6156	UMDMNO.by.GDP_SmoothDer	Derivative of Smoothed Durable Goods (Monthly, NSA) divided by GDP
6157	UMDMNO.by.GDP_Log	Log of Durable Goods (Monthly, NSA) divided by GDP
6158	UMDMNO.by.GDP_mva200	Durable Goods (Monthly, NSA) divided by GDP 200 Day MA
6159	UMDMNO.by.GDP_mva050	Durable Goods (Monthly, NSA) divided by GDP 50 Day MA
6162	DGORDER.by.GDP_YoY5	Durable Goods (Monthly, NSA) divided by GDP 5 Year over 5 Year
6163	DGORDER.by.GDP_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Durable Goods (Monthly, NSA) divided by GDP
6165	DGORDER.by.GDP_SmoothDer	Derivative of Smoothed Durable Goods (Monthly, NSA) divided by GDP
6174	ASHMA.by.GDP_SmoothDer	Derivative of Smoothed Home Mortgages (Quarterly, NSA) divided by GDP
6181	ASHMA.INTEREST_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens
6183	ASHMA.INTEREST_SmoothDer	Derivative of Smoothed Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens
6185	ASHMA.INTEREST_mva200	Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens 200 Day MA
6186	ASHMA.INTEREST_mva050	Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens 50 Day MA
6187	ASHMA.INTEREST.by.GDP_YoY	Year over Year
6190	ASHMA.INTEREST.by.GDP_Smooth	Savitsky-Golay Smoothed (p=3, n=365)
6192	ASHMA.INTEREST.by.GDP_SmoothDer	Derivative of Smoothed
6194	ASHMA.INTEREST.by.GDP_mva200	200 Day MA
6195	ASHMA.INTEREST.by.GDP_mva050	50 Day MA
6199	CONSUMERNSA.INTEREST_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Consumer Loans (Not Seasonally Adjusted) Interest Burdens
6202	CONSUMERNSA.INTEREST_Log	Log of Consumer Loans (Not Seasonally Adjusted) Interest Burdens
6203	CONSUMERNSA.INTEREST_mva200	Consumer Loans (Not Seasonally Adjusted) Interest Burdens 200 Day MA
6204	CONSUMERNSA.INTEREST_mva050	Consumer Loans (Not Seasonally Adjusted) Interest Burdens 50 Day MA
6205	CONSUMERNSA.INTEREST.by.GDP_YoY	Consumer Loans (Not Seasonally Adjusted) Interest Burden Divided by GDP Year over Year
6208	CONSUMERNSA.INTEREST.by.GDP_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Consumer Loans (Not Seasonally Adjusted) Interest Burden Divided by GDP
6210	CONSUMERNSA.INTEREST.by.GDP_SmoothDer	Derivative of Smoothed Consumer Loans (Not Seasonally Adjusted) Interest Burden Divided by GDP
6214	TOTLNNSA_YoY	Total Loans Not Seasonally Adjusted (BUSLOANS+REALLNSA+CONSUMERNSA) Year over Year
6215	TOTLNNSA_YoY4	Total Loans Not Seasonally Adjusted (BUSLOANS+REALLNSA+CONSUMERNSA) 4 Year over 4 Year
6216	TOTLNNSA_YoY5	Total Loans Not Seasonally Adjusted (BUSLOANS+REALLNSA+CONSUMERNSA) 5 Year over 5 Year
6217	TOTLNNSA_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Total Loans Not Seasonally Adjusted (BUSLOANS+REALLNSA+CONSUMERNSA)
6219	TOTLNNSA_SmoothDer	Derivative of Smoothed Total Loans Not Seasonally Adjusted (BUSLOANS+REALLNSA+CONSUMERNSA)
6220	TOTLNNSA_Log	Log of Total Loans Not Seasonally Adjusted (BUSLOANS+REALLNSA+CONSUMERNSA)
6221	TOTLNNSA_mva200	Total Loans Not Seasonally Adjusted (BUSLOANS+REALLNSA+CONSUMERNSA) 200 Day MA
6222	TOTLNNSA_mva050	Total Loans Not Seasonally Adjusted (BUSLOANS+REALLNSA+CONSUMERNSA) 50 Day MA
6223	TOTLNNSA.by.GDP_YoY	Total Loans Not Seasonally Adjusted divided by GDP Year over Year
6224	TOTLNNSA.by.GDP_YoY4	Total Loans Not Seasonally Adjusted divided by GDP 4 Year over 4 Year
6225	TOTLNNSA.by.GDP_YoY5	Total Loans Not Seasonally Adjusted divided by GDP 5 Year over 5 Year
6226	TOTLNNSA.by.GDP_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Total Loans Not Seasonally Adjusted divided by GDP
6228	TOTLNNSA.by.GDP_SmoothDer	Derivative of Smoothed Total Loans Not Seasonally Adjusted divided by GDP
6229	TOTLNNSA.by.GDP_Log	Log of Total Loans Not Seasonally Adjusted divided by GDP
6231	TOTLNNSA.by.GDP_mva050	Total Loans Not Seasonally Adjusted divided by GDP 50 Day MA
6235	TOTLNNSA.INTEREST_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Total Loans Not Seasonally Adjusted Interest Burdens
6236	TOTLNNSA.INTEREST_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15) Total Loans Not Seasonally Adjusted Interest Burdens
6237	TOTLNNSA.INTEREST_SmoothDer	Derivative of Smoothed Total Loans Not Seasonally Adjusted Interest Burdens
6239	TOTLNNSA.INTEREST_mva200	Total Loans Not Seasonally Adjusted Interest Burdens 200 Day MA
6240	TOTLNNSA.INTEREST_mva050	Total Loans Not Seasonally Adjusted Interest Burdens 50 Day MA
6244	TOTLNNSA.INTEREST.by.GDP_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Total Loans Not Seasonally Adjusted Interest Burden Divided by GDP
6245	TOTLNNSA.INTEREST.by.GDP_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15) Total Loans Not Seasonally Adjusted Interest Burden Divided by GDP
6246	TOTLNNSA.INTEREST.by.GDP_SmoothDer	Derivative of Smoothed Total Loans Not Seasonally Adjusted Interest Burden Divided by GDP
6249	TOTLNNSA.INTEREST.by.GDP_mva050	Total Loans Not Seasonally Adjusted Interest Burden Divided by GDP 50 Day MA
6264	EXCSRESNW.by.GDP_SmoothDer	Derivative of Smoothed Excess Reserves of Depository Institutions Divided by GDP
6275	WLRRAL.by.GDP_mva200	Liabilities and Capital: Liabilities: Reverse Repurchase Agreements: Wednesday Level (NSA) Divided by GDP 200 Day MA
6276	WLRRAL.by.GDP_mva050	Liabilities and Capital: Liabilities: Reverse Repurchase Agreements: Wednesday Level (NSA) Divided by GDP 50 Day MA
6280	SOFR99.minus.SOFR1_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Secured Overnight Financing Rate: 99th Percentile - 1st Percentile
6285	SOFR99.minus.SOFR1_mva050	Secured Overnight Financing Rate: 99th Percentile - 1st Percentile 50 Day MA
6286	EXPCH.minus.IMPCH_YoY	U.S. Exports to China (FAS Basis) - U.S. Imports to China (Customs Basis) Year over Year
6287	EXPCH.minus.IMPCH_YoY4	U.S. Exports to China (FAS Basis) - U.S. Imports to China (Customs Basis) 4 Year over 4 Year
6288	EXPCH.minus.IMPCH_YoY5	U.S. Exports to China (FAS Basis) - U.S. Imports to China (Customs Basis) 5 Year over 5 Year
6289	EXPCH.minus.IMPCH_Smooth	Savitsky-Golay Smoothed (p=3, n=365) U.S. Exports to China (FAS Basis) - U.S. Imports to China (Customs Basis)
6291	EXPCH.minus.IMPCH_SmoothDer	Derivative of Smoothed U.S. Exports to China (FAS Basis) - U.S. Imports to China (Customs Basis)
6292	EXPCH.minus.IMPCH_Log	Log of U.S. Exports to China (FAS Basis) - U.S. Imports to China (Customs Basis)
6295	EXPMX.minus.IMPMX_YoY	Year over Year
6300	EXPMX.minus.IMPMX_SmoothDer	Derivative of Smoothed
6301	EXPMX.minus.IMPMX_Log	Log of
6305	SRPSABSNNCB.by.GDP_YoY4	Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) Divided by GDP 4 Year over 4 Year
6306	SRPSABSNNCB.by.GDP_YoY5	Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) Divided by GDP 5 Year over 5 Year
6307	SRPSABSNNCB.by.GDP_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) Divided by GDP
6310	SRPSABSNNCB.by.GDP_Log	Log of Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) Divided by GDP
6313	ASTLL.by.GDP_YoY	All sectors; total loans; liability, Level (NSA) Divided by GDP Year over Year
6318	ASTLL.by.GDP_SmoothDer	Derivative of Smoothed All sectors; total loans; liability, Level (NSA) Divided by GDP
6322	ASFMA.by.GDP_YoY	All sectors; farm mortgages; asset, Level (NSA) Divided by GDP Year over Year
6327	ASFMA.by.GDP_SmoothDer	Derivative of Smoothed All sectors; farm mortgages; asset, Level (NSA) Divided by GDP
6331	ASFMA.by.ASTLL_YoY	All sectors; total loans Divided by farm mortgages Year over Year
6334	ASFMA.by.ASTLL_Smooth	Savitsky-Golay Smoothed (p=3, n=365) All sectors; total loans Divided by farm mortgages
6336	ASFMA.by.ASTLL_SmoothDer	Derivative of Smoothed All sectors; total loans Divided by farm mortgages
6337	ASFMA.by.ASTLL_Log	Log of All sectors; total loans Divided by farm mortgages
6343	ASFMA.INTEREST_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Farm Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens
6345	ASFMA.INTEREST_SmoothDer	Derivative of Smoothed Farm Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens
6347	ASFMA.INTEREST_mva200	Farm Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens 200 Day MA
6348	ASFMA.INTEREST_mva050	Farm Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens 50 Day MA
6349	ASFMA.INTEREST.by.GDP_YoY	Farm Mortgages (Quarterly, NSA) Interest Burden Divided by GDP Year over Year
6352	ASFMA.INTEREST.by.GDP_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Farm Mortgages (Quarterly, NSA) Interest Burden Divided by GDP
6354	ASFMA.INTEREST.by.GDP_SmoothDer	Derivative of Smoothed Farm Mortgages (Quarterly, NSA) Interest Burden Divided by GDP
6357	ASFMA.INTEREST.by.GDP_mva050	Farm Mortgages (Quarterly, NSA) Interest Burden Divided by GDP 50 Day MA
6358	FARMINCOME.by.GDP_YoY	Farm Income (Annual, NSA) Divided by GDP Year over Year
6363	FARMINCOME.by.GDP_SmoothDer	Derivative of Smoothed Farm Income (Annual, NSA) Divided by GDP
6370	BOGMBASE.by.GDP_Smooth	Savitsky-Golay Smoothed (p=3, n=365) BOGMBASE Divided by GDP
6374	BOGMBASE.by.GDP_mva200	BOGMBASE Divided by GDP 200 Day MA
6376	WALCL.by.GDP_YoY	All Federal Reserve Banks: Total Assets Divided by GDP Year over Year
6377	WALCL.by.GDP_YoY4	All Federal Reserve Banks: Total Assets Divided by GDP 4 Year over 4 Year
6378	WALCL.by.GDP_YoY5	All Federal Reserve Banks: Total Assets Divided by GDP 5 Year over 5 Year
6379	WALCL.by.GDP_Smooth	Savitsky-Golay Smoothed (p=3, n=365) All Federal Reserve Banks: Total Assets Divided by GDP
6381	WALCL.by.GDP_SmoothDer	Derivative of Smoothed All Federal Reserve Banks: Total Assets Divided by GDP
6383	WALCL.by.GDP_mva200	All Federal Reserve Banks: Total Assets Divided by GDP 200 Day MA
6384	WALCL.by.GDP_mva050	All Federal Reserve Banks: Total Assets Divided by GDP 50 Day MA
6385	ECBASSETS.by.EUNNGDP_YoY	Central Bank Assets for Euro Area (11-19 Countries) Divided by GDP Year over Year
6388	ECBASSETS.by.EUNNGDP_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Central Bank Assets for Euro Area (11-19 Countries) Divided by GDP
6390	ECBASSETS.by.EUNNGDP_SmoothDer	Derivative of Smoothed Central Bank Assets for Euro Area (11-19 Countries) Divided by GDP
6391	ECBASSETS.by.EUNNGDP_Log	Log of Central Bank Assets for Euro Area (11-19 Countries) Divided by GDP
6400	DGS30TO10_Log	Log of Yield Curve, 30 and 10 Year Treasury (DGS30-DGS10)
6409	DGS10TO1_Log	Log of Yield Curve, 10 and 1 Year Treasury (DGS10-DGS1)
6418	DGS10TO2_Log	Log of Yield Curve, 10 and 2 Year Treasury (DGS10-DGS2)
6424	DGS10TOTB3MS_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Yield Curve, 10 and 3 Month Treasury (DGS10-TB3MS)
6425	DGS10TOTB3MS_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15) Yield Curve, 10 and 3 Month Treasury (DGS10-TB3MS)
6426	DGS10TOTB3MS_SmoothDer	Derivative of Smoothed Yield Curve, 10 and 3 Month Treasury (DGS10-TB3MS)
6427	DGS10TOTB3MS_Log	Log of Yield Curve, 10 and 3 Month Treasury (DGS10-TB3MS)
6429	DGS10TOTB3MS_mva050	Yield Curve, 10 and 3 Month Treasury (DGS10-TB3MS) 50 Day MA
6433	DGS10TODTB3_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Yield Curve, 10 and 3 Month Treasury (DGS10-DTB3)
6435	DGS10TODTB3_SmoothDer	Derivative of Smoothed Yield Curve, 10 and 3 Month Treasury (DGS10-DTB3)
6436	DGS10TODTB3_Log	Log of Yield Curve, 10 and 3 Month Treasury (DGS10-DTB3)
6453	LNU03000000BYPOPTHM_SmoothDer	Derivative of Smoothed Unemployment level (NSA) / Population
6469	NPPTTLBYPOPTHM_Smooth	Savitsky-Golay Smoothed (p=3, n=365) ADP Private Employment / Population
6472	NPPTTLBYPOPTHM_Log	Log of ADP Private Employment / Population
6473	NPPTTLBYPOPTHM_mva200	ADP Private Employment / Population 200 Day MA
6474	NPPTTLBYPOPTHM_mva050	ADP Private Employment / Population 50 Day MA
6480	U6toU3_SmoothDer	Derivative of Smoothed U6RATE minums UNRATE
6489	CHRISCMEHG1.by.PPIACO_SmoothDer	Derivative of Smoothed Copper, $/lb, Normalized by commodities producer price index
6505	DCOILBRENTEU.by.PPIACO_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Crude Oil - Brent, $/bbl, Normalized by producer price index c.o.
6507	DCOILBRENTEU.by.PPIACO_SmoothDer	Derivative of Smoothed Crude Oil - Brent, $/bbl, Normalized by producer price index c.o.
6509	DCOILBRENTEU.by.PPIACO_mva200	Crude Oil - Brent, $/bbl, Normalized by producer price index c.o. 200 Day MA
6514	DCOILWTICO.by.PPIACO_Smooth	Savitsky-Golay Smoothed (p=3, n=365) Crude Oil - WTI, $/bbl, Normalized by producer price index c.o.
6516	DCOILWTICO.by.PPIACO_SmoothDer	Derivative of Smoothed Crude Oil - WTI, $/bbl, Normalized by producer price index c.o.
6517	DCOILWTICO.by.PPIACO_Log	Log of Crude Oil - WTI, $/bbl, Normalized by producer price index c.o.
6518	DCOILWTICO.by.PPIACO_mva200	Crude Oil - WTI, $/bbl, Normalized by producer price index c.o. 200 Day MA
6525	GOLDAMGBD228NLBM.by.PPIACO_SmoothDer	Derivative of Smoothed Gold, USD/Troy OUnce, Normalized by commodities producer price index
6534	GOLDAMGBD228NLBM.by.CPIAUCSL_SmoothDer	Derivative of Smoothed Gold, USD/Troy OUnce, Normalized by consumer price index
6543	GOLDAMGBD228NLBM.by.GDP_SmoothDer	Derivative of Smoothed Gold, USD/Troy OUnce, Normalized by GDP
6550	GSG.Close.by.GDPDEF_Smooth	Savitsky-Golay Smoothed (p=3, n=365) GSCI Commodity-Indexed Trust, Normalized by GDP def
6551	GSG.Close.by.GDPDEF_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15) GSCI Commodity-Indexed Trust, Normalized by GDP def
6553	GSG.Close.by.GDPDEF_Log	Log of GSCI Commodity-Indexed Trust, Normalized by GDP def
6554	GSG.Close.by.GDPDEF_mva200	GSCI Commodity-Indexed Trust, Normalized by GDP def 200 Day MA
6559	GSG.Close.by.GSPC.Close_Smooth	Savitsky-Golay Smoothed (p=3, n=365) GSCI Commodity-Indexed Trust, Normalized by S&P 500
6561	GSG.Close.by.GSPC.Close_SmoothDer	Derivative of Smoothed GSCI Commodity-Indexed Trust, Normalized by S&P 500
6563	GSG.Close.by.GSPC.Close_mva200	GSCI Commodity-Indexed Trust, Normalized by S&P 500 200 Day MA
6572	GDPBYPOPTHM_mva200	GDP/Population 200 Day MA
6581	GDPBYCPIAUCSL_mva200	GDP divided by CPI 200 Day MA
6594	GSPC.CloseBYMDY.Close_YoY5	GSPC by MDY 5 Year over 5 Year
6596	GSPC.CloseBYMDY.Close_Smooth.short	Savitsky-Golay Smoothed (p=3, n=15) GSPC by MDY
6598	GSPC.CloseBYMDY.Close_Log	Log of GSPC by MDY
6599	GSPC.CloseBYMDY.Close_mva200	GSPC by MDY 200 Day MA
6600	GSPC.CloseBYMDY.Close_mva050	GSPC by MDY 50 Day MA
6613	GSPC.DailySwing_Smooth	Savitsky-Golay Smoothed (p=3, n=365) S&P 500 (^GSPC) Daily Swing: (High - Low) / Open
6615	GSPC.DailySwing_SmoothDer	Derivative of Smoothed S&P 500 (^GSPC) Daily Swing: (High - Low) / Open
6616	GSPC.DailySwing_Log	Log of S&P 500 (^GSPC) Daily Swing: (High - Low) / Open
6617	GSPC.DailySwing_mva200	S&P 500 (^GSPC) Daily Swing: (High - Low) / Open 200 Day MA
6618	GSPC.DailySwing_mva050	S&P 500 (^GSPC) Daily Swing: (High - Low) / Open 50 Day MA
6638	HNFSUSNSA.minus.HSN1FNSA_YoY4	Houses for sale - houses sold 4 Year over 4 Year
6639	HNFSUSNSA.minus.HSN1FNSA_YoY5	Houses for sale - houses sold 5 Year over 5 Year
6643	HNFSUSNSA.minus.HSN1FNSA_Log	Log of Houses for sale - houses sold
6644	HNFSUSNSA.minus.HSN1FNSA_mva200	Houses for sale - houses sold 200 Day MA
6645	HNFSUSNSA.minus.HSN1FNSA_mva050	Houses for sale - houses sold 50 Day MA
6649	MSPUS.times.HOUST_Smooth	Savitsky-Golay Smoothed (p=3, n=365) New privately owned units start times median price
6651	MSPUS.times.HOUST_SmoothDer	Derivative of Smoothed New privately owned units start times median price
6652	MSPUS.times.HOUST_Log	Log of New privately owned units start times median price
6653	MSPUS.times.HOUST_mva200	New privately owned units start times median price 200 Day MA
6654	MSPUS.times.HOUST_mva050	New privately owned units start times median price 50 Day MA
6656	MSPUS.times.HNFSUSNSA_YoY4	New privately owned 1-family units for sale times median price 4 Year over 4 Year
6661	MSPUS.times.HNFSUSNSA_Log	Log of New privately owned 1-family units for sale times median price
6662	MSPUS.times.HNFSUSNSA_mva200	New privately owned 1-family units for sale times median price 200 Day MA
6663	MSPUS.times.HNFSUSNSA_mva050	New privately owned 1-family units for sale times median price 50 Day MA
6671	GSPC.Open_mva050_mva200_sig	Sell Signal S&P 500 50 SMA - 200 SMA
6672	MULTPLSP500PERATIOMONTH_Mean	S&P 500 TTM P/E Average (Excludes Values Greater Than 50)

Equities

S&P 500 SMA Trends

Take a look at recent activity in the equities market. This section looks at the S&P 500 close value to the 50 day and 200 day simple moving average (SMA).

This is a longer view for the S&P 500 trend.

Equity indexes normalized by GDP

## Scale for 'y' is already present. Adding another scale for 'y', which will
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The last two years compare favorably with the period around the late 1950’s. Need to dig into this one.

datay <- "GSPC.Close"
ylim <- c(2000, d.GSPC.max)
my.data <- plotSimilarPeriods(df.data, dfRecession, df.symbols, datay, ylim, i.window = 60)
my.data[[1]]

Look at how the different segments of the market move

datay <- "GSPC.CloseBYMDY.Close_YoY"
ylim <- c(-50, 75)
dtStart = as.Date('1980-01-01')
plotSingle(dfRecession, df.data, "date", datay, getPlotTitle(df.symbols, datay), "Date", 
            getPlotYLabel(df.symbols, datay), c(dtStart, Sys.Date()), ylim, TRUE)

datay <- "GSPC.CloseBYMDY.Close"
ylim <- c(0, 20)
dtStart = as.Date('1980-01-01')
plotSingle(dfRecession, df.data, "date", datay, getPlotTitle(df.symbols, datay), "Date", 
            getPlotYLabel(df.symbols, datay), c(dtStart, Sys.Date()), ylim, TRUE)

S&P 500 Normalized moving average

Look at moving average relationship by dividing the S&P 500 open price by the 200 day SMA.

datay <- "GSPC.Open_mva200_Norm"
ylim <- c(50, 125)
dt.start = as.Date('2008-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dt.start)

Crossovers

Look at the 50 DMA versus 200 DMA, often used as a technical indicator of market direction.

datay <- "GSPC.Open_mva050_mva200"
ylim <- c(-200, 200)
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStartBackTest)

datay <- "GSPC.Open_mva050_mva200_sig "
ylim <- c(0.0, 1.0)
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStartBackTest)

S&P 500 TTM P/E

Take a look at some of the earnings trends from SilverBlatt’s sheet.

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Take a longer look back at as-reported and operating earnings

Market prices can out-run earnings so take a look at price to earnings.

Focus on some of the more recent activity

S&P 500 Sales

datay <- "MULTPLSP500SALESQUARTER"
ylim <- c(500, 1500)
dt.start <- as.Date('1999-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dt.start)

datay <- "MULTPLSP500SALESQUARTER"
ylim <- c(500, 1500)
dt.start = as.Date('2001-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dt.start)

Unit Profits

The series peaks in the middle of a bull market.

S&P 500 dividends

12-month real dividend per share inflation adjusted November, 2018 dollars. Data courtesy Standard & Poor’s and Robert Shiller.

https://www.quandl.com/data/MULTPL/SP500_DIV_MONTH-S-P-500-Dividend-by-Month

Evaluate year over year dividend growth.

Real value dividend growth.

datay <- "MULTPLSP500DIVMONTH_YoY"
ylim <- c(-40, 20)
dtStart = as.Date('2001-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart, b.percentile = FALSE)

S&P 500 dividend yield (12 month dividend per share)/price. Yields following September 2018 (including the current yield) are estimated based on 12 month dividends through September 2018, as reported by S&P. Sources: Standard & Poor’s for current S&P 500 Dividend Yield. Robert Shiller and his book Irrational Exuberance for historic S&P 500 Dividend Yields.

https://www.quandl.com/data/MULTPL/SP500_DIV_YIELD_MONTH-S-P-500-Dividend-Yield-by-Month

datay <- "MULTPLSP500DIVYIELDMONTH"
ylim <- c(0, 12)
dtStart = as.Date('1950-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart, b.percentile = FALSE)

datay <- "MULTPLSP500DIVYIELDMONTH"
ylim <- c(1, 4)
dtStart = as.Date('2001-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart, b.percentile = FALSE)

S&P 500 Volume

The log of the S&P volume has some interesting patterns, but nothing that seems to help with a recession indicator.

That is one spiky data series. Not sure there is a lot to help us here.

Russell 2000

Take a look at recent activity in the small cap market.

S&P 500 to Rusell 2000

Thirty day movement

Correlation

## Warning in max.default(structure(numeric(0), class = "Date"),
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## Warning in min.default(structure(numeric(0), class = "Date"),
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## returning Inf

S&P 500 to MDY (Mid-cap) 2000 Correlation

datay1 <- "RLG.Open"
ylim1 <- c(0, 2500)

datay2 <- "MDY.Open"
ylim2 <- c(0, 500)

dtStart <- as.Date("1jan2003","%d%b%Y")

w <- 30
corrName <-
  calcRollingCorr(dfRecession,
                  df.data,
                  df.symbols,
                  datay1,
                  ylim1,
                  datay2,
                  ylim2,
                  w,
                  dtStart)

## Warning in max.default(structure(numeric(0), class = "Date"),
## structure(numeric(0), class = "Date"), : no non-missing arguments to max;
## returning -Inf

## Warning in min.default(structure(numeric(0), class = "Date"),
## structure(numeric(0), class = "Date"), : no non-missing arguments to min;
## returning Inf

Dividend Stocks

This is an interesting series, they should perform better through the recessions. Unfortunately they are short lived so there is not much data so this is more of a place holder for now.

datay <- "NOBL.Open"
ylim <- c(40, 110)
dt.start <- as.Date('2014-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dt.start)

Margin and option data

NYSE Margin Debt

Taking a look at margin debt. NYXDATA stopped providing NYSE margin debt data on Dec 2017. Data is available from FINRA, but it includes more accounts than the data did for NYXdata. I stitched togeter the data sets: data after Jan 2010 include NYSE+Others, data prior is just NYSE account data scaled up to match the FINRA data.

It tends to creep up when there is a frenzy in the stock market.

datay <- "FINRAMarginDebt_Log"
ylim <- c(5, 15)
plotSingleQuick(dfRecession, df.data, datay, ylim)

Take a close look at recent activity

Sometimes it is more helpful to view year over year growth.

More near-term trend.

Take a look at some of the correlations

datay1 <- "FINRAMarginDebt_YoY"
ylim1 <- c(-100, 100)

datay2 <- "GSPC.Close_YoY"
ylim2 <- c(-100, 100)

dtStart <- as.Date("1jan1995","%d%b%Y")

w <- 90
corrName <-
  calcRollingCorr(dfRecession,
                  df.data,
                  df.symbols,
                  datay1,
                  ylim1,
                  datay2,
                  ylim2,
                  w,
                  dtStart)

Comparison to the Russell 2000

datay1 <- "FINRAMarginDebt_YoY"
ylim1 <- c(-100, 100)

datay2 <- "RLG.Close_YoY"
ylim2 <- c(-100, 100)

dtStart <- as.Date("1jan1995","%d%b%Y")

w <- 90
corrName <-
  calcRollingCorr(dfRecession,
                  df.data,
                  df.symbols,
                  datay1,
                  ylim1,
                  datay2,
                  ylim2,
                  w,
                  dtStart)

OCC Options Volumes

See what is happening with the options volumes for equities. (From: https://www.theocc.com/webapps/historical-volume-query)

Looks like options on non-equity co-occurs with peaks/troughs?.

Market Volatility

Take a look at some of the indications of market volatility

CBOE VIX

As markets become complacent (low VIX) and high values, peaks often occur.

Compare the VIX to some of the ETF’s out there.

There

Not much predictive in VIX, take a quick look at the smoothed derivative.

S&P Daily Swings

Daily changes in the S&P should correlate well with the VIX.

More of a correlating series than a predictor.

Employment and payrolls

Unemployment rates

Unemployment rates will probably be useful, let’s take a look at the U-3. The data is a little noisy so there is also a smoothed version plotted. There seems to be a relationship between the unemployment rate and the recessions, but it could be a lagging indicator. This will be explored a little bit more later.

Looking at the unemployment rate, the eye is drawn to the rise and fall of the data, this suggests that the derivative might be helpful as well. The figure below shows the results, using a Savitzky-Golay FIR filter. It looks like the unemployment rate peaks in the middel of the recession. That peak might be a good buy signal.

Continuing Claims

A good measure of how much unemployment is growing.

Continued claims, also referred to as insured unemployment, is the number of people who have already filed an initial claim and who have experienced a week of unemployment and then filed a continued claim to claim benefits for that week of unemployment. Continued claims data are based on the week of unemployment, not the week when the initial claim was filed

https://fred.stlouisfed.org/series/CCNSA

A good measure of how much unemployment is growing

Initial Claims

A good measure of how much unemployment is growing.

An initial claim is a claim filed by an unemployed individual after a separation from an employer. The claim requests a determination of basic eligibility for the Unemployment Insurance program.

https://fred.stlouisfed.org/series/ICSA

Unemployment rates, year-over-year

Both the headline unemployment and U-6 number changes are similar. During the upswing on the cycle it does look like the headline number falls faster than U-6

The second derivative of the unemployment rate does have zero crossings near the middle point of a recession. This would make it a helpful buy signal for the trading strategy.

Unemployment rates, similar periods

Historically the last two years of record low unemployment appear most similar to the 1971-1973 time frame. Just before inflation took off.

Unemployment rates, U-6 and headline number.

Let’s also take a look at the total unemployed, U-6. It continues to fall as the headline number stabilizes as people return to the work force. An indicator the cycle is beginning to top out.

Difference between U6 and U3 to see how close the economy is getting to full employment.

Unemployment and market bottoms

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## replace the existing scale.

Initial jobless claims

We will also take a look at initial jobless claims, this should start to rise just before the unemployment rate.

It looks like the jobless claim tend to peak more towards the end of the recession. It does not seem to be as strong of a sell indicator as the U-3 rate.

Jobless claims have a seasonal component to them. One way to reduce this effect is to calculate year over year growth. That helps some, the peaks seem to be more closely aligned with the middle to end of recessions.

Take a closer look at recent data

## Warning: Removed 1 rows containing missing values (geom_text).

## Warning: Removed 1 rows containing missing values (geom_hline).

Take a look at the percentage of the population looking for work

A bit more recent trend

Unemployment Level

ADP data here. comes out before the official numbers.

Look at the year-over-year change in ADP.

ADP data divided by the population

Payrolls

Look at the BLS data on payrolls. Check the NSA series, then we will look at YoY data.

Hours worked

Sparked by an article at Mises (https://mises.org/wire/how-alexandria-ocasio-cortez-misunderstands-american-poverty), take a look at average weekly hours

The time series is pretty lumpy, plot the YoY change

A more recent look at average weekly hours of production

Industrial Production

Industrial production is also known to fall during an economic downturm, let’s take a look at some of the data from the FRED on industrual production. It does seem to peak prior to a recession so let’s smooth and look at the derivative as it might be a good indicator as well.

Industrial production over the last ten years or so

The derivative isn’t bad, but it sometimes crosses zeros well into a recession. That is less helpful as either a buy or sell indicator. A better measure might year over year (YoY) change.

The year over year change has a similar appearance. The low values at the beginning make the year over year values larger than the more recent values. Seems like it will rank low a reliable indicator.

datay1 <- "INDPRO_YoY"
ylim1 <- c(-20, 12)

datay2 <- "GSPC.Close_YoY"
ylim2 <- c(-100, 50)

dtStart <- as.Date("1jan1981","%d%b%Y")

w <- 360
corrName <- calcRollingCorr(dfRecession, df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

Retail Sales

Retail sales, aggregate

Retail sales also change during recession. As the plot below shows, it seems to follow the trend of industrial production. It might be too strongly correlated to add much to the model. The will be examined in the correlation section.

The derivative of retail sales is a little more erratic than is was the industrial products. Looks like it might be helpful to include in the model as well.

Retail sales, aggregate year-over-year

Take a look at year-over-year changes

Retail sales and unemployment correlations

Let’s see how that looks on year over year basis. Interesting to compare to unemployment rates there appears to a correlation over the long term.

## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.

There is some similarity. The rolling correlation shows the inverse relationship prior to a recession.

datay1 <- "RSALESAGG_YoY"
ylim1 <- c(-12.5, 7.5)

datay2 <- "UNEMPLOY_YoY"
ylim2 <- c(-30, 100)

dtStart <- as.Date("1jan1970","%d%b%Y")

w <- 180
corrName <- calcRollingCorr(dfRecession,df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

Retail sales correlation and industrial production

Industrial production and retail sales look very similar so the plot below shows the 360 correlation. The corerlation does tend to fall around a recession, although 2008 was so bad that they both fell together. Not sure if it is that useful.

datay1 <- "INDPRO"
ylim1 <- c(40, 125)

datay2 <- "RSALESAGG"
ylim2 <- c(100000, 200000)

dtStart <- as.Date("1jan1981","%d%b%Y")

w <- 30
corrName <- calcRollingCorr(dfRecession, df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

It is interesting to see the strong correlation; however, I suspect this is due to more to the shape of the trends. How do the YoY correlations look? They are a little less correlated, probably better to use in the machine learning later.

datay1 <- "INDPRO_YoY"
ylim1 <- c(-20, 20)

datay2 <- "RSALESAGG_YoY"
ylim2 <- c(-20, 20)

dtStart <- as.Date("1jan1981","%d%b%Y")

w <- 30
corrName <- calcRollingCorr(dfRecession, df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

Advance Retail Sales

This is an advanced estimate of the retail sales value.

Also take a look at year over year

Retail sales and the labor market

Income

Real Personal Income

Real Personal Income (Excluding Transfer, Annual)

During a recession real personal income falls. In the plot the peaks can be seen prior to each recession.

datay <- "W875RX1"
ylim <- c(3000, 15000)
plotSingleQuickModern(datay, ylim)

The features we are interested in are the peaks and valleys so we’ll use the derivative to get to those. Interesting, there is usually a first zero crossing before a recession and a second during or just after the recession.

Real personal income might have some seasonal variance, but it seems the year over year change tells the same story.

Price and cost measures

This section shows price and cost measures.

Two commonly used indexes are the CPI (consumer price index) and PPI (producer price index). CPI tries to show final prices paid for goods and services by urban U.S. consumers. This index includes sales tax and imports. The PPI attempts to reflect the prices paid at all stages of production, including goods and services purchases as inputs as well as goods and services purchased by consumers from retail and producer sellers. The PPI does not include imports or sales tax. The CPI reflects all rebates and financing plans wherease the PPI reflects only those rebate and financing plans provided by the producer. For example if an automotive manufacturer offers a rebate of $500 and the dealer offers an additional rebate of $500 then the PPI would reflect only the automotive manufacturer rebate, but the CPI would reflect both rebates.

Sources; https://www.bls.gov/opub/hom/pdf/cpihom.pdf and https://www.bls.gov/opub/hom/pdf/ppi-20111028.pdf.

Consumer price index

What does CPI look like?

datay <- "CPIAUCSL"
ylim <- c(0, 300)
plotSingleQuickModern(datay, ylim)

Check out the YoY growth

datay <- "CPIAUCSL_YoY"
ylim <- c(-2, 15)
plotSingleQuickModern(datay, ylim)

CPI to PPI

Suggested by Charlie, it can be helpful to look at the relationship between producer prices and consumer prices.

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Producer Price Index (Commodities)

Commodities

Basket

Take a look at some trends of baskets of commodities.

This plot examines commodity performance relative to the GDP deflator

Crude oil

Look at a trend of West Texas Intermediate (WTI)

This is ticker data from yahoo

Take a look at both WTI and Brent crude.

Real price of crude using producer price index for commodities

Gold

As risks increase investors often flock to safe haven assets like gold. An up-tick in prices can indicate investor uncertainty. This can be seen in the nominal price plot around 1980 and again in 2007.

This plots out the real price of gold by two different deflators. PPI corrected price is a little higher, to be expected since CPI also includes the effects of sales tax and imports. The spike in 1980 is especially pronounced in this series.

See how nominal and real prices look year over year. From the long-term view seems like there is little difference in the three series. Although not shown, even over the near-term there is little difference in the series.

See how gold correlates with the VIX. Both gold and VIX should respond to investor axiety, but it doesn’t look like it correlates very well.

## `geom_smooth()` using formula 'y ~ x'

## Warning: Removed 245 rows containing non-finite values (stat_smooth).

Copper

Dr. Copper has a reputation as an indicator of economic malaise, but it does not seem to have much of a correlation with the recessions. The series below is from CME via Quandl. It has a lot of data so I am also looking at the smoothed version.

Copper is one of the commodities in the PPI so it is a bit of a proxy for how copper is doing relative to the basket of commodities.

The change in prices, year over year, do generally peak prior to a recession. The time and shape of this peak varies, but it still might be helpful. A couple of the large troughs do seem to correlate with the end of the recession. Likely this is because industrial production has also fallen.

There is some correlation between copper and the smooth recession initiator, especially at the end of the recession.

Might be easier to see correlation in a dot plot format.

## `geom_smooth()` using formula 'y ~ x'

## Warning: Removed 342 rows containing non-finite values (stat_smooth).

This is a legacy series from FRED. It has not been updated in a couple of years so I am assuming it will go away.

Oil Services

Amazing events in the first half of 2020, take a look at those

See how the players are doing

Federal Reserve

The federal reserve has an impact on the economy, here are some data series relating to that.

Little bit closer

datay <- "WALCL"
ylim <- c(0, 8500)
dtStart = as.Date('2003-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

Federal Reserve Reverse Repo Agreements

Compare liabilities to reverse repo trends

Spiky, might be easier to look at year-over-year

Normalized by GDP

datay <- "WLRRAL.by.GDP"
ylim <- c(0, 4)
dtStart = as.Date('2003-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

Overnight Bank Funding Rate

“The overnight bank funding rate is calculated using federal funds transactions and certain Eurodollar transactions. The federal funds market consists of domestic unsecured borrowings in U.S. dollars by depository institutions from other depository institutions and certain other entities, primarily government-sponsored enterprises, while the Eurodollar market consists of unsecured U.S. dollar deposits held at banks or bank branches outside of the United States. U.S.-based banks can also take Eurodollar deposits domestically through international banking facilities (IBFs). The overnight bank funding rate (OBFR) is calculated as a volume-weighted median of overnight federal funds transactions and Eurodollar transactions reported in the FR 2420 Report of Selected Money Market Rates. Volume-weighted median is the rate associated with transactions at the 50th percentile of transaction volume. Specifically, the volume-weighted median rate is calculated by ordering the transactions from lowest to highest rate, taking the cumulative sum of volumes of these transactions, and identifying the rate associated with the trades at the 50th percentile of dollar volume. The published rates are the volume-weighted median transacted rate, rounded to the nearest basis point.” https://www.newyorkfed.org/markets/obfrinfo.

Secured Overnight Financing Rate

“The Secured Overnight Financing Rate (SOFR) is a broad measure of the cost of borrowing cash overnight collateralized by Treasury securities. The SOFR includes all trades in the Broad General Collateral Rate plus bilateral Treasury repurchase agreement (repo) transactions cleared through the Delivery-versus-Payment (DVP) service offered by the Fixed Income Clearing Corporation (FICC), which is filtered to remove a portion of transactions considered “specials” " https://apps.newyorkfed.org/markets/autorates/sofr

Take a look at the variation (99th - 1st percentile)

Reserve Balances with Federal Reserve Banks

Hard to get a sense of these series in the absolute. Take a look relative to GDP.

By double entry book-keeping reserves+loans (assets) = deposit (liabilities). Does that really work?

Correlation Between Reserves and Total Loans

As reserves increase there should be less lending. That correlation generally holds.

## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.

Did the reserve balances increase after the 2016 and 2018 drops? Not in the same way. There are some relationships between the equities market and the reserves though.

Explicitly correlate reserve balances and total loans. It is a weak and noisy correlation.

## `geom_smooth()` using formula 'y ~ x'

## Warning: Removed 990 rows containing non-finite values (stat_smooth).

Interest on excess reserves

Monetary Base

Currency trend, base

This used to trend along with GDP. It doesn’t anymore.

Money supplies

Basic currency trend (currency component of M1)

datay <- "WCURRNS_YoY"
dtStart = as.Date('1980-01-01')
ylim <- c(0, 17)
myplot <- plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)
myplot

datay <- "WCURRNS_YoY"
dtStart = as.Date('2000-01-01')
ylim <- c(0, 20)
myplot <- plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)
myplot

The rate of change of money supply could be an indicator of a recession. Let’s see how that compares.

Intervention in the repo market

The federal reserve provides liquidity to the repo market, summary of that action

European central bank

The European central band (ECB) has taken a different path compared to the US Federal Reserve bank.

## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.

Federal Debt

The government is a big driver of the economy, let’s see what it is doing in the debt markets.

datay <- "GFDEBTN"
ylim <- c(0, 28000000)
plotSingleQuick(dfRecession, df.data, datay, ylim)

datay <- "GFDEBTN_Log"
ylim <- c(12, 18)
plotSingleQuick(dfRecession, df.data, datay, ylim)

datay <- "GFDEBTN_YoY"
ylim <- c(-10, 25)
plotSingleQuick(dfRecession, df.data, datay, ylim)

Federal debt as percent GDP

datay <- "GFDEGDQ188S"
ylim <- c(30, 150)
plotSingleQuick(dfRecession, df.data, datay, ylim)

Federal deficit as percent GDP

datay <- "FYFSGDA188S"
ylim <- c(-30, 5)
plotSingleQuick(dfRecession, df.data, datay, ylim)

Charlie Hatch has a nice format of deficit versus debt:

## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.

Nonfinancial Corporate Business Debt

What about Nonfinancial corporate business and debt securities? Hopefully this doesn’t follow the business loan trends.

That is crazy steep. Time for a log format, see if that brings out the peaks and troughs. That’s a litte better, it looks like there might be a change in slope prior to the recessions.

The derivative doesn’t seem to be much help. There is not much correlation between the zero crossings and the NEBR recessions.

Debt cycle

This analysis roughly follows the ideas in Big Debt Crises book by Ray Dalio.

Total loans

One business cycle theory describes recessions as a market adjustment to mis-allocated assets, often fueled by an credit expansion. That makes the volume of loans an interesting feature to look at. In the presentation of data it looks like the great recession had the largest impact.

Plotting the year over year growth rate helps pull out those small changes in the early years in the data. Peaks can be seen prior to most recessions.

Zoom in to the last couple of decades

As long term interest rates rise, loans should start to tick down. To check this, the total loans and 10 to 1 year spreads are plotted. This is generally the trend observed.

There is a good correlation between these two variables. This next section plots that correction explicitly.

Total loans as percent of GDP

This is the total loans. I think the picture is too broad to point to a specific sector of the economy. The debt burden assumes interest rates are tied to the 10-year treasury: (TOTLNNSA * DGS10) / 100

Commercial and industral loans

Business loans should slow before the recession (a contraction in credit as rates rise).

Commercial and industrial loans as percent of GDP and and income

Look at business debt normalized by GDP over the entire time series. This ratio often peaks at the mid-point of a recession.

https://www.wsj.com/articles/this-isnt-your-fathers-corporate-bond-market-11590574555

“Bonds are behaving more like bank debt, which tends to remain stable or even increase at the onset of recessions, as lenders keep distressed clients afloat—and only later turn off the taps. This was confirmed by a recent report from the Bank for International Settlements. It also found a tight link between this lending cycle and the “real” economy’s booms and busts."

I assume that interest is related to the 10-year treasure: (TOTCINSA * DGS10) / 100

Farm loans

See how the farming sector is fairing.

Real estate loans

Data taken from H.8 Assets and Liabilities of Commercial Banks in the United States. Take a look at SA and NSA data series as weekly and month updates. It should all be similar at this scale.

This gives a big picture, but makes it hard to connect the loans with the income needed to cover those loans. In the next section, loans will be broken up by commercial and residential.

Real Estate (Residential)

In absolute terms the mortgages have increased, but it does not appear to be out of line with the overall economy.

Normalized by GDP it is easier to see the peak in 2008 and that loan levels appear reasonable at the commercial banks.

Maybe the GSE’s are making loans. Take a look at the total mortgages from Z.1 as a percentage of GDP. That does not look too far off trend (ignoring that peak in 2008).

I am assuming that personal income is paying for the mortgages.

Real estate (residential) as percent of GDP and and income

## Warning: Removed 1 rows containing missing values (geom_text).

Consumer loans

Focusing on the consumer sector the growth in debt and incomes can be directly compared. Personal income, as a percent of GDP, remains nearly constant. It is not uncommon for the personal income to rise prior to a recession. Likely this reflect increasing asset prices and market returns. Also interesting to see the loans pick up after interest rates dropped in 1982.

Consumer loans as percent of GDP and and income

Take a closer look since the 2008 recession. Looks like loans are starting to slow as the interest burden rises and incomes remain stable. There are some anomolies in the A065RC1A027NBEA data series because it only updates onces a year. the PI series updates once a month but is noisier and seasonally adjusted. It also shows incomes rising in the middle of the 2008 recession, which doesn’t seem to be accurate.

## Warning: Removed 1 rows containing missing values (geom_text).

## Warning: Removed 1 rows containing missing values (geom_text).

## Warning: Removed 1 rows containing missing values (geom_hline).

Repo market

This market went through some stress in 2008, it is happening again so setup some plots to watch it.

Nonfincial corporate business security repo asset level

Bonds

T-Bills and Yield Curve

Speaking of loans, interest rates also play into this. This analysis will focus on treasure bills. The 3-month is plotted below. The yield flattens before a recession as investors go long on bonds and short on equities.

datay <- "TB3MS"
datay.aux <- "DTB3"
ylim <- c(0, 20)
p1 <- plotSingleQuickModern(datay, ylim)
p1 + geom_line(data=df.data, aes_string(x="date", y=datay.aux, colour=shQuote(datay.aux)), na.rm = TRUE)

datay <- "TB3MS"
datay.aux <- "DTB3"
ylim <- c(0, 2.5)
dtStart = as.Date('2017-01-01')
p1 <- plotSingle(dfRecession, df.data, "date", datay, getPlotTitle(df.symbols, datay), "Date", 
            getPlotYLabel(df.symbols, datay), c(dtStart, Sys.Date()), ylim, TRUE)
p1 + geom_line(data=df.data, aes_string(x="date", y=datay.aux, colour=shQuote(datay.aux)), na.rm = TRUE)

Check out LIBOR and fed funds rate

The 1-year is plotted below. The yield flattens before a recession as investors go long on bonds and short on equities.

datay <- "DGS10"
datay.aux <- "TNX.Close"
ylim <- c(0, 20)
p1 <- plotSingleQuickModern(datay, ylim)
p1 + geom_line(data=df.data, aes_string(x="date", y=datay.aux, colour=shQuote(datay.aux)), na.rm = TRUE)

Close in, the trend towards inversion be more easily seen. I am also comparing data from the CBOE as well as FRED.

Bond yields are a good proxy for interest rates. As rates rise the theory goes that loans should decrease (inverse correlation).

And a longer window

The yield curve (30 year bond rate minus the 10 year bond rate) may not be a good recession indicator, but a collapse is not good (https://blogs.wsj.com/moneybeat/2018/04/30/theres-more-than-one-part-of-the-yield-curve-getting-flatter/).

The yield curve (10 year bond rate minus the 1 year bond rate) seems to a good indicator of an oncoming recession. It could be a buy indicator by itself.

More recent data

Just the last 24 months or so.

Plot the 10 Year to 3 month over a few decades to see what the outling cases look like

The last two year compare favorably with the period around the 2015-2016 turndown, driven primarily by slowing of the Chinese GDP. Not a debt-driven cycle.

This plot format was suggested by a mises.org article (https://mises.org/wire/yield-curve-accordion-theory), but they only went back to 1988. The date seemed arbitrary so I went back further in time.

Take a look at more recent data

Try looking at a 1-year average of the above time series

High quality bonds

datay <- "AAA"
ylim <- c(2.5, 10)
dtStart = as.Date('1997-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

High quality bonds to 10-year treasury

High quality bonds long-term trend.

datay <- "DGS10ByAAA"
ylim <- c(1, 6.0)
dtStart = as.Date('1967-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

High quality bonds near-term trend.

datay <- "DGS10ByAAA"
ylim <- c(1, 6.0)
dtStart = as.Date('2007-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

High yield spread

“This data represents the Option-Adjusted Spread (OAS) of the ICE BofAML US Corporate A Index, a subset of the ICE BofAML US Corporate Master Index tracking the performance of US dollar denominated investment grade rated corporate debt publicly issued in the US domestic market. This subset includes all securities with a given investment grade rating A. The ICE BofAML OASs are the calculated spreads between a computed OAS index of all bonds in a given rating category and a spot Treasury curve. An OAS index is constructed using each constituent bond‚Äôs OAS, weighted by market capitalization. When the last calendar day of the month takes place on the weekend, weekend observations will occur as a result of month ending accrued interest adjustments.”

• ICE Benchmark Administration Limited (IBA), ICE BofAML US Corporate A Option-Adjusted Spread [BAMLC0A3CA], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/BAMLC0A3CA, July 4, 2019.

datay <- "BAMLC0A3CA"
ylim <- c(0, 7)
dtStart = as.Date('1997-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

Municipal bond market

Suggest by a WSJ article, change in volume for high-risk muni’s. Doesn’t look like there is much too it yet.

https://www.wsj.com/articles/risky-municipal-bonds-are-on-a-hot-streak-11558949401?mod=hp_lead_pos3

datay <- "HYMB.Close"
ylim <- c(40, 62)
dtStart = as.Date('2011-01-01')
p1 <- plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

p1 <-
  p1 + geom_vline(
    xintercept = as.Date("2015-08-24"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )

p1 <-
  p1 + geom_vline(
    xintercept = as.Date("2016-01-08"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )
p1 <-
  p1 + geom_vline(
    xintercept = as.Date("2018-02-05"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )
p1 <-
  p1 + geom_vline(
    xintercept = as.Date("2018-10-11"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )

datay <- "HYMB.Volume"
ylim <- c(0, 1750000)
p1.vol <- plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

p1.vol <-
  p1.vol + geom_vline(
    xintercept = as.Date("2015-08-24"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )

p1.vol <-
  p1.vol + geom_vline(
    xintercept = as.Date("2016-01-08"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )
p1.vol <-
  p1.vol + geom_vline(
    xintercept = as.Date("2018-02-05"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )
p1.vol <-
  p1.vol + geom_vline(
    xintercept = as.Date("2018-10-11"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )


datay <- "GSPC.Open"
datay_aux <- "GSPC.Close"
ylim <- c(1500, d.GSPC.max )
p2 <-
  plotSingle(
    dfRecession,
    df.data,
    "date",
    datay,
    getPlotTitle(df.symbols, datay),
    "Date",
    getPlotYLabel(df.symbols, datay),
    c(dtStart, Sys.Date()),
    ylim,
    TRUE
  )

p2 <-
  p2 + geom_vline(
    xintercept = as.Date("2015-08-24"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )
p2 <-
  p2 + geom_vline(
    xintercept = as.Date("2016-01-08"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )
p2 <-
  p2 + geom_vline(
    xintercept = as.Date("2018-02-05"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )
p2 <-
  p2 + geom_vline(
    xintercept = as.Date("2018-10-11"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )


grid.arrange(p1,
             p1.vol,
             p2,
             ncol = 1,
             top = "High Yield Muni's and S&P Price")

Total Loans and yield curve correlation

This relationship was suggest by Charlie and it is an interesting one. As the yield curve flattens (10-year and 1-year rates converge), total loans grow. The generalization is not always accurate, but it does fit.

## `geom_smooth()` using formula 'y ~ x'

I wanted to see how this looked compared to the 3 month

## `geom_smooth()` using formula 'y ~ x'

## Warning: Removed 282 rows containing non-finite values (stat_smooth).

Consumer loans and yield curve correlation

Compared to business loans, consumer loans seem to have to response to the 10Y to 3M yield curve.

## `geom_smooth()` using formula 'y ~ x'

## Warning: Removed 311 rows containing non-finite values (stat_smooth).

Business loans and yield curve correlation

## `geom_smooth()` using formula 'y ~ x'

## Warning: Removed 104 rows containing non-finite values (stat_smooth).

That’s pretty good correlation. Let’s see what the rolling correlation looks like.

datay1 <- "TOTLNNSA_YoY"
ylim1 <- c(-10, 20)

datay2 <- "DGS10TO1"
ylim2 <- c(-5, 10)

dtStart <- as.Date("1jan1960","%d%b%Y")

w <- 360
corrName <- calcRollingCorr(dfRecession, df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

datay1 <- "TOTLNNSA_YoY"
ylim1 <- c(-10, 20)

datay2 <- "DGS10TO1"
ylim2 <- c(-5, 10)

dtStart <- as.Date("1jan1960","%d%b%Y")

w <- 720
corrName <- calcRollingCorr(dfRecession, df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

One other items, let’s see how loans do versus the federal funds rate

## `geom_smooth()` using formula 'y ~ x'

Baker Hughes Rig Count

BEA Supplemental Estimates, Motor Vehicles

Definitions

Autos–all passenger cars, including station wagons.
Light trucks–trucks up to 14,000 pounds gross vehicle weight, including minivans and
sport utility vehicles. Prior to the 2003 Benchmark Revision light trucks were up to 10,000 pounds.
Heavy trucks–trucks more than 14,000 pounds gross vehicle weight.
Prior to the 2003 Benchmark Revision heavy trucks were more than 10,000 pounds.
Domestic sales–United States (U.S.) sales of vehicles assembled in the U.S., Canada, and Mexico.
Foreign sales–U.S. sales of vehicles produced elsewhere.
Domestic auto production–Autos assembled in the U.S.
Domestic auto inventories–U.S. inventories of vehicles assembled in the U.S., Canada, and Mexico.

TAble 6 - Light Vehicle and Total Vehicle Sales

Auto sales

A WSJ article suggested that auto sales might be a good indicator so bring that to the mix. It does have troughs that correlate with recessions

There might be some seasonal variance in the auto sales so lets take a look at the year over year. The data is pretty noisy, it probably will not make a very good indicator.

BEA Gross Domestic Product

Data in this section come from the Bureau of Economic Analysis.

Table 1.1.5. Gross Domestic Product

[Billions of dollars] Seasonally adjusted at annual rates

A191RC: Gross Domestic Product - Line 1

GDP numbers tend to lag so this series is truly an afterthought. But it does have some correlation with the recessions.

GDP does not reflect the capacity of the economy nor the efficiency. Shrinking capacity and lower prices at constant volumes would indicate improvements in effeciency/productivity which is good for the economy, but does not move the GDP upward.

Looks like the year over year change on the GDP should correlate well with unemployment.

Table 1.1.9. Implicit Price Deflators for Gross Domestic Product

[Index numbers, 2012=100] Seasonally adjusted

A191RD: Gross Domestic Product - Line 1

This is GDP price deflator series.

GDP normalized by CPI

Normalize GDP by CPI

Economic yield curve (GDP to 1-year treasury)

GDP versus the yield on the 1-year. This series was prompted by an article suggesting that the “economic yield curve” should be used to indicate a recession rather than an inverted yield curve. Less of indicator and more of concurrent confirmation of recession. Not sure why they would be related either.

Economic yield curve (GDP to 3-month treasury)

Same idea as above, but applied the 3-month treasury.This one has fewer false triggers, but is not as helpful as 10Y to 3M spread in predicting a recession.

A824RC: National defense Federal Gov’t Expenditures - Line 24

U.S. Bureau of Economic Analysis, Federal Government: National Defense Consumption Expenditures and Gross Investment [FDEFX], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/FDEFX, April 6, 2021.

A825RC: Nondefense Federal Gov’t Expenditures - Line 25

U.S. Bureau of Economic Analysis, Federal Government: Nondefense Consumption Expenditures and Gross Investment [FNDEFX], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/FNDEFX, April 6, 2021.

Table 6.16D. Corporate Profits by Industry

Select series from Table 6.16D

A051RC: Corporate profits with inventory and capital consumption adjustment

From BEA’s documentation (https://www.bea.gov/media/5671):

“BEA’s featured measure of corporate profits — profits from current production - provides a comprehensive and consistent economic measure of the income earned by all U.S. corporations. As such, it is unaffected by changes in tax laws, and it is adjusted for nonreported and misreported income. It excludes dividend income, capital gains and losses, and other financial flows and adjustments, such as deduction for “bad debt.” Thus, the NIPA measure of profits is a particularly useful analytical measure of the health of the corporate sector. For example, in contrast to other popular measures of corporate profits, the NIPA measure did not show the large run-up in profits during the late 1990s that was primarily attributable to capital gains.

Profits after tax with IVA and CCAdj is equal to corporate profits with IVA and CCAdj less taxes on corporate income. It provides an after-tax measure of profits from current production."

Data is Line 1 of Table 6.16D

A053RC: Corporate profits without inventory and capital consumption adjustment

Profits look a bit flat over the last several years in this series.

Table 2.6. Personal Income and Its Disposition, Monthly

Billions of dollars; months are seasonally adjusted at annual rates.

A065RC Personal Income - Line 1

BEA Account Code: A065RC

Personal income is the income that persons receive in return for their provision of labor, land, and capital used in current production and the net current transfer payments that they receive from business and from government.25 Personal income is equal to national income minus corporate profits with inventory valuation and capital consumption adjustments, taxes on production and imports less subsidies, contributions for government social insurance, net interest and miscellaneous payments on assets, business current transfer payments (net), current surplus of government enterprises, and wage accruals less disbursements, plus personal income receipts on assets and personal current transfer receipts. A Guide to the National Income and Product Accounts of the United States (NIPA) - (http://www.bea.gov/national/pdf/nipaguid.pdf)

Suggested Citation: U.S. Bureau of Economic Analysis, Personal Income [PI], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/PI, July 11, 2019.

DPCERC: Personal consumption expenditures (PCE) - Table 2.1, Line 29

BEA Account Code: DPCERC Personal consumption expenditures (PCE) is the primary measure of consumer spending on goods and services in the U.S. economy. 1 It accounts for about two-thirds of domestic final spending, and thus it is the primary engine that drives future economic growth. PCE shows how much of the income earned by households is being spent on current consumption as opposed to how much is being saved for future consumption. -https://www.bea.gov/system/files/2019-12/Chapter-5.pdf

Suggested Citation: U.S. Bureau of Economic Analysis, Personal Consumption Expenditures [PCE], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/PCE, June 12, 2020

DPCERG: Personal consumption expenditures Price Index (PCEPI) - Table 2.1, Line 29

BEA Account Code: DPCERG The gross domestic product price index measures changes in prices paid for goods and services produced in the United States, including those exported to other countries. Prices of imports are excluded. The gross domestic product implicit price deflator, or GDP deflator, basically measures the same things and closely mirrors the GDP price index, although the two price measures are calculated differently. The GDP deflator is used by some firms to adjust payments in contracts.

The gross domestic purchases price index is BEA’s featured measure of inflation for the U.S. economy overall. It measures changes in prices paid by consumers, businesses, and governments in the United States, including the prices of the imports they buy.

BEA’s closely followed personal consumption expenditures price index, or PCE price index, is a narrower measure. It looks at the changing prices of goods and services purchased by consumers in the United States. It’s similar to the Bureau of Labor Statistics’ consumer price index for urban consumers. The two indexes, which have their own purposes and uses, are constructed differently, resulting in different inflation rates.

The PCE price index is known for capturing inflation (or deflation) across a wide range of consumer expenses and for reflecting changes in consumer behavior. For example, if the price of beef rises, shoppers may buy less beef and more chicken. Also, BEA revises previously published PCE data to reflect updated information or new methodology, providing consistency across decades of data that’s valuable for researchers. The PCE price index is used primarily for macroeconomic analysis and forecasting. -https://www.bea.gov/resources/learning-center/what-to-know-prices-inflation

Suggested Citation: U.S. Bureau of Economic Analysis, Personal Consumption Expenditures: Chain-type Price Index [PCEPI], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/PCEPI, April 25, 2021.

A072RC: Personal Savings Rate - Line 35

Consumers tend to pull down their savings rates as unemployment decreases and market conditions improve. This series has tended to be unreliable due to the size of revisions during the comprehensive update carried out by the BEA. The last update on this series moved the rate from 4.2 to 6.7 percent.

(https://www.bloomberg.com/news/articles/2018-07-27/americans-have-been-saving-much-more-than-thought-new-data-show)

BEA Account Code: A072RC Personal saving as a percentage of disposable personal income (DPI), frequently referred to as “the personal saving rate,” is calculated as the ratio of personal saving to DPI. Personal saving is equal to personal income less personal outlays and personal taxes; it may generally be viewed as the portion of personal income that is used either to provide funds to capital markets or to invest in real assets such as residences.(https://www.bea.gov/national/pdf/all-chapters.pdf) A Guide to the National Income and Product Accounts of the United States (NIPA).

Suggested Citation: U.S. Bureau of Economic Analysis, Personal Saving Rate [PSAVERT], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/PSAVERT, July 9, 2019.

Take a closer look at the last decade

The relationship between personal savings and unemployment (U-3) can be better visualized with a scatter plot

## `geom_smooth()` using formula 'y ~ x'

## Warning: Removed 190 rows containing non-finite values (stat_smooth).

The fit does not explain most of what is in the plot. Lets take a look at the rolling correlation.

datay1 <- "UNRATE"
ylim1 <- c(2, 12)

datay2 <- "PSAVERT"
ylim2 <- c(0, 35)

dtStart <- as.Date("1jan1985","%d%b%Y")

w <- 360
corrName <- calcRollingCorr(dfRecession, df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

Personal savings to household net worth

A relationship between personal savings and household networth can be seen in a scatter plot. This was suggested by a WSJ article (https://blogs.wsj.com/dailyshot/2018/02/23/the-daily-shot-reasons-for-declining-u-s-household-savings-rate/).

## `geom_smooth()` using formula 'y ~ x'

## Warning: Removed 529 rows containing non-finite values (stat_smooth).

U.S. Census Bureau

U.S. International Trade in Goods and Services (FT900)

U.S. Bureau of Economic Analysis and U.S. Census Bureau, U.S. Imports of Goods by Customs Basis from China [IMPCH], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/IMPCH, October 5, 2019.

New Houses Sold and For Sale by Stage of Construction and Median Number of Months on Sales Market

Read an article suggesting that housing sales and sales growth could be useful. FRED only has new home data so start there.

datay <- "HSN1FNSA"
ylim <- c(0, 200)
dtStart = as.Date('1964-01-01')
p1 <- plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

datay <- "HNFSUSNSA"
ylim <- c(0, 600)
p2 <- plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

datay <- "HNFSUSNSA.minus.HSN1FNSA"
ylim <- c(0, 600)
p3 <-
  plotSingle(
    dfRecession,
    df.data,
    "date",
    datay,
    getPlotTitle(df.symbols, datay),
    "Date",
    getPlotYLabel(df.symbols, datay),
    c(dtStart, Sys.Date()),
    ylim,
    TRUE
  )

grid.arrange(p1,
             p2,
             p3,
             ncol = 1,
             top = "New Housing Sales")

New housing yoy

New Privately-Owned Housing Units Authorized in Permit-Issuing Places

As provided by the Census, start occurs when excavation begins for the footings or foundation of a building. All housing units in a multifamily building are defined as being started when this excavation begins. Beginning with data for September 1992, estimates of housing starts include units in structures being totally rebuilt on an existing foundation.

Suggested Citation: U.S. Census Bureau and U.S. Department of Housing and Urban Development, Housing Starts: Total: New Privately Owned Housing Units Started [HOUST], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/HOUST, June 13, 2020.

Take a look at privately owned starts

New Privately-Owned Houses Sold and For Sale

Suggested Citation: U.S. Census Bureau and U.S. Department of Housing and Urban Development, Median Sales Price of Houses Sold for the United States [MSPUS], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/MSPUS, June 13, 2020.

Finally, take a look at starts times the median price

Durable Goods

Suggested Citation: U.S. Census Bureau, Manufacturers’ New Orders: Durable Goods [UMDMNO], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/UMDMNO, April 26, 2021.

Durable goods, not seasonally adjusted, divided by GDP

Durable goods, seasonally adjusted, divided by GDP

Federal reserve board H.8: Assets and Liabilities of Commercial Banks in the United States

Page 4: Not Seasonally adjusted, billions of dollars

Commercial and industrial loans, all commercial banks - Line 10

Data taken from H.8 Assets and Liabilities of Commercial Banks in the United States. Take a look at SA and NSA data series as weekly and month updates. It should all be similar at this scale.

Suggested Citation: Board of Governors of the Federal Reserve System (US), Commercial and Industrial Loans, All Commercial Banks [BUSLOANS], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/BUSLOANS, July 11, 2019.

Taking a look at the difference in SA and NSA series. Seasonal adjustments do vary, but do not seem to be related to recessions.

The raw series is just too steep for any kind of machine learnine. This needs to be converted to log scale.

That’s a little better, let’s see what the smoothed derivative looks like.

That is odd…looks like this doesn’t cross zero unless we are getting close to, or into, a recession. The year over year tells about the same story. Might be a good indication of the end of a recession.

Consumer loans, all commercial banks - Line 20

Suggested Citation: Board of Governors of the Federal Reserve System (US), Consumer Loans, All Commercial Banks [CONSUMERNSA], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/CONSUMERNSA, July 11, 2019.

That spike in consumer loans is due to

“April 9, 2010 (Last revised September 23, 2011): As of the week ending March 31, 2010, domestically chartered banks and foreign-related institutions had consolidated onto their balance sheets the following assets and liabilities of off-balance-sheet vehicles, owing to the adoption of FASB’s Financial Accounting Statements No. 166 (FAS 166),”Accounting for Transfers of Financial Assets," and No. 167 (FAS 167), “Amendments to FASB Interpretation No. 46(R).”

This included a consumer loans, credit cards and other revolving plans change of $321.9B. That was a lot of off-balance-sheet bank assets.

Deposits, All Commercial Banks, all commercial banks - Line 34

Data taken from H.8 Assets and Liabilities of Commercial Banks in the United States. Take a look at SA and NSA data series as weekly and month updates. It should all be similar at this scale.

Suggested Citation: Board of Governors of the Federal Reserve System (US), Deposits, All Commercial Banks [DPSACBW027SBOG], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/DPSACBW027SBOG, May 14, 2020.

Federal reserve board Z.1: Financial Accounts of the United States

From the FRED website (https://fred.stlouisfed.org/release?rid=52):

"The Financial Accounts (formerly known as the Flow of Funds accounts) are a set of financial accounts used to track the sources and uses of funds by sector. They are a component of a system of macroeconomic accounts including the National Income and Product accounts (NIPA) and balance of payments accounts, all of which serve as a comprehensive set of information on the economy’s performance.(1) Some important inferences that can be drawn from the Financial accounts are the financial strength of a given sector, new economic trends, changes in the composition of wealth, and development of new financial instruments over time.(1)

Sectors are compiled into three categories: households, nonfinancial businesses, and banks. The sources of funds for a sector are its internal funds (savings from income after consumption) and external funds (loans from banks and other financial intermediaries). (1) Funds for a given sector are used for its investments in physical and financial assets. Dividing sources and uses of funds into two categories helps the staff of the Federal Reserve System pay particular attention to external sources of funds and financial uses of funds.(2) One example is whether households are borrowing more from banks—or in other words, whether household debt is rising. Another example might be whether banks are using more of their funds to provide loans to consumers. Transactions within a sector are not shown in the accounts; however, transactions between sectors are.(2) Monitoring the external flows of funds provides insights into a sector’s health and the performance of the economy as a whole.

Data for the Financial accounts are compiled from a large number of reports and publications, including regulatory reports such as those submitted by banks, tax filings, and surveys conducted by the Federal Reserve System.(2) The Financial accounts are published quarterly as a set of tables in the Federal Reserve’s Z.1 statistical release.

1. Teplin, Albert M. “The U.S. Flow of Funds Accounts and Their Uses.” Federal Reserve Bulletin, July 2001; http://www.federalreserve.gov/pubs/bulletin/2001/0701lead.pdf.
2. Board of Governors of the Federal Reserve System. “Guide to the Flow of Funds Accounts.” 2000, http://www.federalreserve.gov/apps/fof/."

L.102 Nonfinancial Business

FL102051003.Q: Nonfinancial corporate business; security repurchase agreements; asset

Asset level of nonfinancial business security repo agreements. federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL102051003&t=

L.214 Loans

FL894123005.Q: All sectors; total loans; liability

Sum of domestic financial sectors, all sectors, total mortgages, and households/non-profits. federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL894123005&t=L.107&bc=L.107:FL793068005&suf=Q

FL793068005.Q: Domestic financial sectors; depository institution loans n.e.c.; asset

Sum of Monetary authority; depository institution loans n.e.c.; asset and Private depository institutions; depository institution loans n.e.c.; asset. federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL793068005&t=L.214&suf=Q

FL893169005.Q: All sectors; other loans and advances; liability

Sum of finance, government, and chartered institutions asset levels. https://www.federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL893169005&t=L.214&suf=Q

FL893065005.Q: All sectors; total mortgages; asset

https://www.federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL893065005&t=L.214&suf=Q

FL893065105.Q: All sectors; home mortgages; asset

https://www.federalreserve.gov/apps/fof/DisplayTable.aspx?t=L.214

FL893065405.Q: All sectors; multifamily residential mortgages; asset

https://www.federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL893065405&t=L.214&suf=Q

FL893065505.Q: All sectors; commercial mortgages; asset

https://www.federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL893065505&t=L.214&suf=Q

FL893065603.Q: All sectors; farm mortgages; asset

https://www.federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL893065603&t=L.214&suf=Q

FL153166000.Q: Households and nonprofit organizations; consumer credit; liability

federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL153166000&t=L.214&suf=Q

B.101 Balance Sheet of Households and Nonprofit Organizations

FL152000005.Q: Households and nonprofit organizations; total assets, Level

string.source ID: FL152000005.Q.

FL152090006.Q: Household Net Worth as Percentage of Disposable Personal Income

string.source ID: FL152090006.Q. Household networth tends to fall as a recession start.

Productivity Yield Curve

GDP versus productivity

Manufacturing output and employees

Not sure if these relates to a recession, but fascinating to see how output and employees change with time.

datay <- "OUTMS"
ylim <- c(60, 120)
dtStart = as.Date('1987-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

datay <- "MANEMP"
ylim <- c(10000, 20000)
dtStart = as.Date('1948-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

datay <- "PRS30006163"
ylim <- c(40, 120)
dtStart = as.Date('1986-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

Shipping volumes might be helpful in determining state of the economy.

datay <- "FRGSHPUSM649NCIS"
ylim <- c(0.8, 1.4)
dtStart = as.Date('1999-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

datay <- "FRGSHPUSM649NCIS_YoY"
ylim <- c(-30, 30)
dtStart = as.Date('1999-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

Freight, loosely, moves inversely to the trade deficit.

datay <- "BOPGTB_YoY"
ylim <- c(-30, 30)
dtStart = as.Date('1999-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

World bank air transportation. Only updated annually so less usefull, but interesting reference to above.

datay <- "WWDIWLDISAIRGOODMTK1"
ylim <- c(0, 250000)
dtStart = as.Date('1999-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

Gross private domestic investment

Spending most certainly tips down prior to a recession. The gross private domestic investment data series, plotted in log format below, show how private investment pulls back prior to recessions.

The change in direction is a little easier to see if the derivative is plotted, first YoY then the smoothed derivative

Velocity

Productivity

Date range to match census data

PMI

Industrial Production

This is a look at manufacturing industrial production. The yoY change should be a leading indicator of unemployment.

Housing

Take a look at housing starts. These can drop as rates rise.

Case-schiller price index

Population data

Many of the economic series can be better understood if normalized by population. Basic population and worker data from FRED.

Population to GDP

Look at GDP divided by CPI per person. It flattens and even dips a little prior to a recession. Might be worth looking at the derivative of this series.

That is worth a closer look

datay1 <- "GDPBYCPIAUCSLBYPOPTHM_SmoothDer"
ylim1 <- c(-5, 5)

datay2 <- "RecInit_Smooth"
ylim2 <- c(0, 1)

dtStart <- as.Date("1jan1960","%d%b%Y")

w <- 30
corrName <- calcRollingCorr(dfRecession, df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

Correlation Study

Detailed correlations are explored above. Before concluding, let’s take a look at some overall correlation values to see if anything pops out.

Commodities

As mentioned above, copper, year over year, has some correlation with the recession initiation. It could be useful.

GDP Series

GDP, normalized first by CPI and then by population, looks like it migh correlate inversely with the recession indicators

Financials

Let’s see where we are so far. The correlation plot confirms some of the speculation above. The S&P 500 (GSPC.Open) is well correlated with industrial production (INDPRO), business loans (BUSLOANS), total loans (TOTLNNSA) , and nonfinancial corporate business debt (NCBDBIQ027S).

In this case, I want and indicator that rises prior to a recession. It looks like the unemployment rate (UNRATE), real personal income (W875RX1), and the yield curve (DGS10TO1) are all inversely correlated with the recession initiation indicator.

I thought the modified recession initiation would be a harder match, but there are quite a few correlated variables. Lets take a look at some of those in more detail

Complete list of symbols

Since it is tedious to do this one at a time, all the symbols were entered into a data frame, loaded, and aggregated together in a single xts object.

This is the complete list of symbol names and sources used in the project.